Ghidra MCP Server

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A production-ready Model Context Protocol (MCP) server that bridges Ghidra's powerful reverse engineering capabilities with modern AI tools and automation frameworks. 209 MCP tools, battle-tested AI workflows, and the most comprehensive Ghidra-MCP integration available — now including P-code emulation, live debugger integration, and PCode-graph data flow analysis.

Why Ghidra MCP?

Most Ghidra MCP implementations give you a handful of read-only tools and call it a day. This project is different — it was built by a reverse engineer who uses it daily on real binaries, not as a demo.

209 MCP tools — 3x more than any competing implementation. Not just read operations — full write access for renaming, typing, commenting, structure creation, script execution, P-code emulation, and live debugging.
Battle-tested AI workflows — Proven documentation workflows (V5) refined across hundreds of functions. Includes step-by-step prompts, Hungarian notation reference, batch processing guides, and orphaned code discovery.
Production-grade reliability — Atomic transactions, batch operations (93% API call reduction), configurable timeouts, and graceful error handling. No silent failures.
Cross-binary documentation transfer — SHA-256 function hash matching propagates documentation across binary versions automatically. Document once, apply everywhere.
Full Ghidra Server integration — Connect to shared Ghidra servers, manage repositories, version control, checkout/checkin workflows, and multi-user collaboration.
Headless and GUI modes — Run with or without the Ghidra GUI. Docker-ready for CI/CD pipelines and automated analysis at scale.
Opinionated by design — v5.0 moves naming conventions, type safety, and documentation standards into the tool layer. AI agents and human engineers produce consistent output without style guides in every prompt.

Convention Enforcement

You've been there: six months into a project you find ProcessItem, process_items, handleItem, and ItemProc in the same codebase — four functions doing the same thing, named by four different sessions or engineers with no shared contract. Fixing it takes longer than it should, and the problem will happen again.

v5.0 moves conventions from "things to remember" into the tool layer, where they can actually be enforced.

Tier	Behavior	Example
Auto-fix	Applied silently	`count` field on a `uint32` → auto-prefixed `dwCount` on save
Warn	Change goes through, warning returned	`processData` → "name should be PascalCase with a verb: `ProcessData`"
Reject	Change blocked with explanation	`undefined → undefined` type change → "no-op rejected, type unchanged"

For AI agents, this means consistent output across every session, every model, every run — without pasting a style guide into every prompt. The tool knows the rules; the model just needs to make the call.

For teams, it eliminates the entire class of review comment that says "that's not our naming convention." Convention arbitration stays in the tool, not in code review.

For solo work at scale, analyze_function_completeness gives you a 0–100% score that measures honestly: structural deductions (unfixable compiler artifacts) are forgiven in your effective score, log-scaling prevents one bad category from burying everything else, and tiered plate comment quality means you know exactly what's missing and why.

🌟 Features

Core MCP Integration

Full MCP Compatibility — Complete implementation of Model Context Protocol
209 MCP tools — Comprehensive API surface covering every aspect of binary analysis
Production-Ready Reliability — Atomic transactions, batch operations, configurable timeouts
Real-time Analysis — Live integration with Ghidra's analysis engine

Compatibility note: MCP tool names are normalized for GitHub Copilot CLI and CAPI validation. Exposed tool names use lowercase letters, digits, underscores, and hyphens only; nested HTTP paths such as /debugger/status are advertised as names like debugger_status_2 when needed to avoid collisions with static bridge tools.

Binary Analysis Capabilities

Function Analysis — Decompilation, call graphs, cross-references, completeness scoring
Data Flow Analysis — PCode-graph value propagation (forward / backward) from any variable or register
Data Structure Discovery — Struct/union/enum creation with field analysis and naming suggestions
String Extraction — Regex search, quality filtering, and string-anchored function discovery
Import/Export Analysis — Symbol tables, external locations, ordinal import resolution
Memory & Data Inspection — Raw memory reads, byte pattern search, array boundary detection
Cross-Binary Documentation — Function hash matching and documentation propagation across versions

Dynamic Analysis (v5.4.0)

P-code Emulation — Run any function in isolation via Ghidra's EmulatorHelper; brute-force API hash resolution in milliseconds
Live Debugger Integration — 16 /debugger/* endpoints over Ghidra's TraceRmi framework (GUI plugin only; dbgeng on Windows PE, gdb/lldb otherwise): launch, interrupt/resume, step into/over/out, breakpoints, registers, memory reads, stack traces, ASLR-aware static↔dynamic address translation. The bridge can also proxy 22 debugger_* tools to an external debugger server; they are opt-in (see below)

AI-Powered Reverse Engineering Workflows

Function Documentation Workflow V5 — 7-step process for complete function documentation with Hungarian notation, type auditing, and automated verification scoring
Batch Documentation — Parallel subagent dispatch for documenting multiple functions simultaneously
Orphaned Code Discovery — Automated scanner finds undiscovered functions in gaps between known code
Data Type Investigation — Systematic workflows for structure discovery and field analysis
Cross-Version Matching — Hash-based function matching across different binary versions

Development & Automation

Ghidra Script Execution — List and run Ghidra scripts, or run inline script code, via MCP (running them is opt-in: GHIDRA_MCP_ALLOW_SCRIPTS=1)
Multi-Program Support — Switch between and compare multiple open programs
Batch Operations — Bulk renaming, commenting, typing, and label management (93% fewer API calls)
Headless Server — Full analysis without Ghidra GUI — Docker and CI/CD ready
Project & Version Control — Create projects, manage files, Ghidra Server integration
Analysis Control — List, configure, and trigger Ghidra analyzers programmatically

🚀 Quick Start

Prerequisites

Java 21 LTS (OpenJDK recommended)
Apache Maven 3.9+ for the python -m tools.setup commands below (Maven is their default backend). Not needed if you build with the committed Gradle wrapper instead — see step 6
Ghidra 12.1.4 (or compatible version)
Python 3.10+ with uv (recommended) or pip + venv

Shared Ghidra Server users: Ghidra 12.1.4 clients require a Ghidra Server at 12.1, 12.0.5, or a newer compatible version. Upgrade the server before using this plugin from a 12.1 client.

Ghidra 12.1.4 ships Jython as an optional extension. Java scripts work by default, but .py scripts in ghidra_scripts/ require installing the Jython extension from File > Install Extensions and restarting Ghidra.

Installation

Recommended for all platforms: use python -m tools.setup directly.

ensure-prereqs installs runtime Python requirements plus the Ghidra JARs needed in the local Maven repository. deploy copies the build output, installs the user-profile extension, and patches Ghidra user config.

Clone the repository:

git clone https://github.com/bethington/ghidra-mcp.git
cd ghidra-mcp

Recommended: run environment preflight first:

python -m tools.setup preflight --ghidra-path "F:\ghidra_12.1.4_PUBLIC"

Build and deploy to Ghidra:
```
python -m tools.setup ensure-prereqs --ghidra-path "F:\ghidra_12.1.4_PUBLIC"
python -m tools.setup build
python -m tools.setup deploy --ghidra-path "F:\ghidra_12.1.4_PUBLIC"
```
deploy saves/closes an already-running matching Ghidra instance when needed, installs the extension, starts Ghidra, waits for MCP health, and runs schema smoke checks.

Prefer to click through Ghidra's own dialogs, or installing a release zip on a machine without the repo? Follow the illustrated manual GUI install guide.

Optional strict/manual mode (advanced):

# Skip automatic prerequisite setup
python -m tools.setup build
python -m tools.setup deploy --ghidra-path "F:\ghidra_12.1.4_PUBLIC"

Show command help:
```
python -m tools.setup --help
```

Optional build-only mode (advanced/troubleshooting):

python -m tools.setup build

Two Java backends are supported. Gradle is the default for local work — it reads Ghidra's jars straight out of the installation, so there is no install-file step and nothing to install beyond a JDK. CI builds and gates with Maven, so Maven is a maintained peer rather than a fallback.

# Gradle (default) -- the wrapper is committed, so no Gradle install is needed.
# -PGHIDRA_INSTALL_DIR or the GHIDRA_INSTALL_DIR env var both work.
# In Git Bash use forward slashes; a backslash path is mangled before Gradle sees it.
./gradlew buildExtension -PGHIDRA_INSTALL_DIR=/path/to/ghidra

# Maven (peer backend; what CI uses). Needs Ghidra's jars in the local .m2 first:
#   python -m tools.setup ensure-prereqs --ghidra-path /path/to/ghidra
mvn clean package assembly:single -DskipTests

python -m tools.setup build routes to Maven by default; set TOOLS_SETUP_BACKEND=gradle to route it to Gradle instead.

Installation (Linux — Ubuntu/Debian)

Clone the repository:

git clone https://github.com/bethington/ghidra-mcp.git
cd ghidra-mcp

Install system prerequisites (if not already installed):
```
sudo apt update && sudo apt install -y openjdk-21-jdk maven python3 python3-pip python3-venv curl jq unzip
```
Debian/Kali/Ubuntu 23.04+ note (PEP 668): these distros mark the system Python as externally managed, so a bare pip install fails with error: externally-managed-environment. Don't work around it with --break-system-packages — it can corrupt apt-managed tooling. Instead use uv (recommended — it creates and manages a project-local .venv automatically, and is what this repo's commands use):
```
curl -LsSf https://astral.sh/uv/install.sh | sh
uv run bridge-mcp-ghidra    # resolves deps into .venv and starts the bridge
```
or a classic virtual environment:
```
python3 -m venv .venv && source .venv/bin/activate
pip install -e .
bridge-mcp-ghidra
```

Run environment preflight:

python -m tools.setup preflight --ghidra-path ~/ghidra_12.1.4_PUBLIC

Build and deploy to Ghidra (single command):
```
python -m tools.setup ensure-prereqs --ghidra-path ~/ghidra_12.1.4_PUBLIC
python -m tools.setup build
python -m tools.setup deploy --ghidra-path ~/ghidra_12.1.4_PUBLIC
```
This will:
- Install Ghidra JAR dependencies into your local ~/.m2/repository
- Build GhidraMCP-<version>.zip with Maven
- Extract the extension to ~/.config/ghidra/ghidra_<version>_PUBLIC/Extensions/
- Update preferences with LastExtensionImportDirectory
- Install Python requirements

Optional: setup only Maven dependencies:

python -m tools.setup install-ghidra-deps --ghidra-path ~/ghidra_12.1.4_PUBLIC

Show command help:
```
python -m tools.setup --help
```

Linux paths: The extension is installed to $HOME/.config/ghidra/ghidra_<version>_PUBLIC/Extensions/GhidraMCP/. Ghidra config files are in $HOME/.config/ghidra/ghidra_<version>_PUBLIC/.

Installation (macOS — Homebrew)

Install prerequisites:

brew install openjdk@21 maven python ghidra

Clone the repository:

git clone https://github.com/bethington/ghidra-mcp.git
cd ghidra-mcp

Install Ghidra JARs into local Maven:

 python -m tools.setup install-ghidra-deps \
    --ghidra-path /opt/homebrew/opt/ghidra/libexec

Build and deploy:
```
 python -m tools.setup ensure-prereqs \
    --ghidra-path /opt/homebrew/opt/ghidra/libexec
 python -m tools.setup build
 python -m tools.setup deploy \
    --ghidra-path /opt/homebrew/opt/ghidra/libexec
```
The extension is installed to ~/Library/ghidra/ghidra_12.1.4_PUBLIC/Extensions/GhidraMCP/.

Note: the Homebrew path contains no version string, so tools.setup reads the Ghidra version from Ghidra/application.properties inside the installation instead.
Start Ghidra and enable the plugin:
```
/opt/homebrew/opt/ghidra/libexec/ghidraRun
```
The server starts with the plugin. Check it from the project window: Tools > GhidraMCP > Server Status
Configure Cursor/Claude MCP (~/.cursor/mcp.json) — use the absolute path to uv (which uv), not the bare name; GUI-launched clients do not inherit your shell's PATH (#441):
```
{
  "mcpServers": {
    "ghidra": {
      "command": "/opt/homebrew/bin/uv",
      "args": ["run", "--directory", "/path/to/ghidra-mcp", "bridge-mcp-ghidra"]
    }
  }
}
```
macOS is the sharpest case: apps launched from Finder/Dock get launchd's PATH, which never contains ~/.local/bin or /opt/homebrew/bin.

Installation (Arch Linux — AUR)

@Pandoriaantje maintains community AUR packages:

ghidra-mcp-git — tracks main
ghidra-mcp — tracks tagged releases

Install with your AUR helper of choice, e.g.:

yay -S ghidra-mcp        # or ghidra-mcp-git

Basic Usage

Option 1: Stdio Transport (Recommended for AI tools)

uv run bridge-mcp-ghidra          # or: python -m bridge_mcp_ghidra

MCP client config (.mcp.json, ~/.cursor/mcp.json, Claude Desktop config, …). Use the absolute path to uv — see the note below for why:

{
  "mcpServers": {
    "ghidra-mcp": {
      "command": "/home/<you>/.local/bin/uv",
      "args": ["run", "--directory", "/path/to/ghidra-mcp", "bridge-mcp-ghidra", "--transport", "stdio"],
      "env": { "GHIDRA_MCP_URL": "http://127.0.0.1:8089" }
    }
  }
}

On Windows the same config points at uv.exe, e.g. "command": "C:\\Users\\<you>\\.local\\bin\\uv.exe". Find your own path with which uv (POSIX) or where.exe uv (Windows), or just run python -m tools.setup preflight, which prints the resolved absolute path and a ready-to-paste snippet.

Why absolute? "command": "uv" fails under service and GUI launchers. The MCP client resolves command with its own PATH, not your shell's. A client started from a systemd user service, a .desktop entry, or any other GUI session inherits that launcher's environment, which routinely lacks ~/.local/bin and ~/.cargo/bin — the very directories uv installs into. The failure lands at process-spawn time as spawn uv ENOENT, before any bridge code runs, so there is nothing in any log to read. An absolute path makes the client's PATH irrelevant and works on the first try. The same applies to python, python3, and the bridge-mcp-ghidra console script. (#441)

To add the bridge to Autohand Code from a cloned checkout:

autohand mcp add ghidra /home/<you>/.local/bin/uv run --directory /path/to/ghidra-mcp bridge-mcp-ghidra

Add --scope project before ghidra to save the server in the current project's .autohand configuration instead of your user configuration.

Option 2: Streamable HTTP Transport (Recommended for web/HTTP clients)

uv run bridge-mcp-ghidra --transport streamable-http --mcp-host 127.0.0.1 --mcp-port 8081

MCP client config for the HTTP transport (add to your client's MCP config file):

{
  "mcpServers": {
    "ghidra-mcp-http": {
      "url": "http://127.0.0.1:8081/mcp"
    }
  }
}

Browser-based clients (e.g. MCP Inspector) work out of the box: the HTTP transports answer CORS preflight (OPTIONS) requests and expose the mcp-session-id / mcp-protocol-version headers to scripts. Allowed origins mirror the Host-header policy — loopback on any port is always permitted, plus the bind host and any hosts listed in GHIDRA_MCP_ALLOWED_HOSTS.

GHIDRA_MCP_ALLOWED_HOSTS also supports clients that route a loopback-bound bridge through another network namespace. For example, a container can address the host as host.containers.internal without exposing the bridge on a LAN interface:

GHIDRA_MCP_ALLOWED_HOSTS=host.containers.internal \
  uv run bridge-mcp-ghidra --transport streamable-http \
  --mcp-host 127.0.0.1 --mcp-port 8081

The setting extends DNS-rebinding Host/Origin validation only; it does not change the bind address or make the listener reachable on additional interfaces.

Option 3: SSE Transport (Deprecated — use streamable-http instead)

uv run bridge-mcp-ghidra --transport sse --mcp-host 127.0.0.1 --mcp-port 8081

Bridge advanced flags

Flag	Default	Description
`--transport`	`stdio`	`stdio` (AI tools), `streamable-http` (web clients), `sse` (deprecated)
`--mcp-host`	`127.0.0.1`	Bind host for HTTP transports
`--mcp-port`	—	Port for HTTP transports
`--lazy`	(default)	Load only the default tool groups on connect, and let the model pull in the rest with `search_tools`/`load_tool_group`.
`--no-lazy`	off	Load all tool groups immediately on connect. Needed only by MCP clients that ignore `tools/list_changed`; rejected outright by the Gemini API (see below).
`--default-groups`	`listing,function,program`	Comma-separated groups loaded on connect under `--lazy`.
`--tools-page-size`	`0`	Serve `tools/list` in pages of this size (`0` = one page). Only for a client that cannot take one large response; a client that ignores `nextCursor` sees only the first page.
`--json-response`	off	streamable-http: answer POSTs with plain JSON instead of an SSE stream. Server-initiated messages such as `tools/list_changed` are then not delivered.
`--stateless-http`	off	streamable-http: no session id and no server-initiated notifications, for running several bridge workers behind a load balancer. Pair it with `--no-lazy`, since a group loaded later can never be announced.

To require a token from MCP clients of an HTTP transport, set GHIDRA_MCP_INBOUND_TOKEN=<secret>; clients must then send Authorization: Bearer <secret>. The bridge logs a warning when it binds a non-loopback --mcp-host without one. Separately, when GHIDRA_MCP_AUTH_TOKEN (the token the bridge sends to Ghidra) is set and the bridge binds a non-loopback host, clients must present that same token, so the bridge cannot be used to relay it.

Lazy tool loading is the default (issue #440)

Advertising all 209 endpoints in a single tools/list is over a hard limit for at least one major provider. Gemini compiles function declarations into a constrained-decoding state machine and rejects the whole request before any tool is ever called:

400 INVALID_ARGUMENT
The specified schema produces a constraint that has too many states for serving

That is not a degradation, it is an outright break, and no client-side setting could work around a server that only ever offered the full set. So the bridge now loads listing,function,program (68 endpoints plus the 8 static tools) on connect and registers the rest on demand.

If your client ignores tools/list_changed it will not notice tools that are registered later, and should turn lazy loading off:

uv run bridge-mcp-ghidra --no-lazy          # when you control the command line
export GHIDRA_MCP_LAZY=0                    # when you don't (Docker, uvx, some client configs)

GHIDRA_MCP_LAZY accepts 0/false/no/off and 1/true/yes/on; an explicit --lazy/--no-lazy on the command line wins over it. Startup logs which mode is in effect.

Strict program routing (multi-program safety)

Set GHIDRA_MCP_REQUIRE_PROGRAM_SELECTORS=1 to make the bridge refuse any program-scoped call that omits a program selector, returning a clear error instead of letting the call ride the server's shared "current program" (the one switch_program and the active GUI tab move).

export GHIDRA_MCP_REQUIRE_PROGRAM_SELECTORS=1
uv run bridge-mcp-ghidra

Without this, a call that leaves program= out runs against whichever program is current, which is fine for a single-program workflow but a hazard once several programs are open: the call can read or edit the wrong binary with no error. The hazard is worse when more than one client shares a server, since each one moves that current-program global out from under the others.

With strict mode on, every program-scoped call must name its target. This covers every selector that picks an open program: plain program= and the cross-program tools' source_program/target_program or program_a/program_b (declared required, but the server still falls back to the current program when one arrives empty). A forgotten selector surfaces as a loud error on the first bad call instead of a silent write to the wrong binary. Tools with no program selector (open_program and close_program take path/name) are unaffected. Off by default: with the variable unset the bridge sends calls unchanged.

Reducing tool-context overhead

The bridge exposes a large catalog, so it loads only listing,function,program on connect (see above) and lets the model discover the rest on demand instead of registering everything:

search_tools("rename function") — keyword-search the entire catalog, including tools whose group isn't loaded. Each result says whether it's callable now and, if not, the exact load_tool_group(...) call to enable it.
list_tool_groups() — list all categories and their load state.
load_tool_group("datatype") / unload_tool_group("datatype") — load or drop a category at runtime.
check_tools("rename_symbol,batch_set_comments") — confirm specific tools are callable right now.

search_tools works in both lazy and --no-lazy modes, so agents that honor tools/list_changed get full discovery without the upfront context cost.

Minimal read-only allowlist

Some MCP clients gate tools through an explicit allowlist. Cut it too far and the agent loses discovery — it cannot find entry points or enumerate functions through MCP, so it works around the allowlist by curl-ing the HTTP API on 127.0.0.1:8089 directly, which defeats the point of having one. The allowlist has to be small and self-sufficient.

Minimum viable read-only set (4 tools):

Tool	Group	What it buys you
`get_metadata`	`program`	Which binary is loaded — name, architecture, image base, function count. Orientation, and it confirms the bridge reached Ghidra at all.
`find_functions`	`listing`	Paginated function enumeration (`offset`, `limit`); with no filter it lists the whole program, and `name_pattern`/`regex` turn it into a name search. This is the discovery tool — without it the agent cannot answer "what is in this binary".
`get_entry_points`	`listing`	Where execution starts, so analysis has a root to work down from.
`get_functions`	`function`	The payload. Takes `function=` (name or address) or `functions=` (comma-separated names or addresses, up to 20), and `fields=` to pick what comes back: `decompiled_code`, `signature`, `callers`, `callees`, `xrefs`, `comments`, and more.

That set is genuinely closed: get_entry_points and find_functions supply the addresses and names that get_functions consumes, and its callees field names the next functions to feed straight back into it.

The three tools suggested in #441 were get_metadata, get_entry_points and decompile_function. The first two still exist under those names; decompile_function was folded into get_functions in 7.0.0 (fields=decompiled_code), and the migration guide maps every other removed name. find_functions is the one addition worth making: without it the agent can only reach code that is reachable by name from something it already decompiled, so anything not referenced from an entry point is invisible.

Useful next additions, in order:

Tool	Group	Why
`get_function_call_graph`	`xref`	A multi-level call graph (`depth`, `direction`) in one call. One level of callers and callees already comes from `get_functions`.
`get_xrefs_to`	`xref`	Who touches this address — the standard question about a global. Takes `addresses=` for several at once.
`list_strings`	`listing`	Strings are the cheapest orientation signal in an unknown binary.
`list_program_items`	`listing`	`kind=imports` / `kind=exports`: the binary's external surface. Other kinds list segments, classes, namespaces, data items and external locations.

Every tool above is a GET; none of them writes to the Ghidra database.

Two things to check when your allowlist is narrow:

Groups, not just names. The bridge registers tools by group, and the group is the category on the Java @McpTool annotation (which the running server publishes at /mcp/schema) — not the category field in tests/endpoints.json, which is a separate hand-maintained column and does not always agree. All four tools in the minimum set fall inside the default listing,function,program groups, so they are registered even under --lazy. Of the additions above, only the xref ones fall outside: under --lazy you must either allow load_tool_group as well, or start the bridge with --default-groups listing,function,program,xref.
A narrow allowlist plus --lazy needs the group tools. If you allowlist only leaf tools and run lazily, the agent has no way to load anything else. Either run eagerly (--no-lazy; lazy is the default) or add search_tools, list_tool_groups, load_tool_group, and check_tools to the allowlist.

Verify any allowlist against the running server rather than against this table: curl http://127.0.0.1:8089/mcp/schema lists every tool with the category the bridge groups it by.

Optional: Connect an external debugger server

The bridge can proxy 22 debugger_* tools to an external dbgeng/WinDbg debugger server speaking the bridge's debugger HTTP API. That server is not part of this repository; this repo ships only the proxies. They are off by default and register only when you opt in:

# point the bridge at your debugger server (loopback only)
export GHIDRA_DEBUGGER_URL=http://127.0.0.1:8099

# or force registration against the default URL (http://127.0.0.1:8099)
export GHIDRA_DEBUGGER_TOOLS=1

GHIDRA_DEBUGGER_TOOLS decides outright when set: 1/true/yes/on registers the tools, anything else (0, false, ...) keeps them off even with a URL configured. With neither variable set the tools simply do not appear, rather than appearing and failing. The host platform plays no part.

Ghidra's own TraceRmi debugger endpoints (debugger_status, debugger_launch, ...) are separate: they live in the GUI plugin and need no extra server.

Calls are only ever proxied to a loopback URL (127.0.0.1, localhost or ::1), so a non-loopback GHIDRA_DEBUGGER_URL does not register the tools. To reach a debugger server on another machine, forward its port to loopback (for example an SSH tunnel) and point GHIDRA_DEBUGGER_URL there.

The bridge reads these from its own process environment (the MCP client's env block, or your shell); it does not read a .env file.

In Ghidra

Start Ghidra and open your project
In the project window, enable the plugin via File > Configure > Utility > Configure > GhidraMCPPlugin (this is what deploy does; enabling it in CodeBrowser also works, but then the server runs only while CodeBrowser is open)
Optional: configure a custom port via Edit > Tool Options > GhidraMCP HTTP Server in the same window
The server starts with the plugin; check it via Tools > GhidraMCP > Server Status
The server runs on http://127.0.0.1:8089/ by default

Screenshots of every step: docs/INSTALL_GUI.md.

Verify It's Working

# Quick health check
curl http://127.0.0.1:8089/check_connection
# Expected: {"status": "ok", "server_kind": "gui", "version": "7.0.0", "program": "<name>"}
# ("program" appears only while a program is current)

# Fuller health: build details, uptime, open program count, HTTP pool, memory
curl http://127.0.0.1:8089/mcp/health

# Every tool the server advertises
curl -s http://127.0.0.1:8089/mcp/schema | jq '.tools | length'

Support This Project

If Ghidra MCP saves you engineering or reverse-engineering time, consider sponsoring the project.

One-time sponsorship helps fund fixes, compatibility updates, and release work.
Recurring sponsorship helps keep maintenance, docs, and production hardening moving.
Company support helps prioritize long-term reliability for the bridge, headless server, debugger integration, and workflow tooling.

🔒 Security

GhidraMCP is designed for localhost-only development. The default configuration — HTTP server bound to 127.0.0.1, no authentication — is safe on a trusted single-user workstation and matches pre-v5.4.1 behavior.

If you expose the server beyond loopback, configure these three environment variables first. The server refuses to start on a non-loopback bind without a token.

Env var	Effect
`GHIDRA_MCP_AUTH_TOKEN`	When set, every HTTP request must carry `Authorization: Bearer <token>`. Timing-safe comparison. `/mcp/health` and `/check_connection` are exempt.
`GHIDRA_MCP_ALLOW_SCRIPTS`	Set to `1`, `true`, or `yes` to enable `/run_script_inline` and `/run_ghidra_script`. Off by default as of v5.4.1 — these endpoints execute arbitrary Java against the Ghidra process. In headless mode this also triggers OSGi `BundleHost` initialization at server startup (Felix framework, ~hundreds of ms); leave it off if you don't need script execution.
`GHIDRA_MCP_FILE_ROOT`	When set to a directory path, filesystem-path endpoints (`/import_file`, `/open_project`, `/delete_file`, etc.) canonicalize the input and require it to fall under this root. Prevents path-traversal.

Name-quality enforcement is separate from security. By default, rename_function and global write endpoints reject names that fail the built-in quality gates, and struct field writes apply the built-in field prefix convention. Disable the built-in convention layer with Edit > Tool Options > GhidraMCP HTTP Server > Strict Naming Enforcement. The same Tool Options checkbox covers rename_symbol (all symbol kinds), set_global, the apply_data_type prefix/type guard, and struct-field Hungarian prefix auto-fixes in create_struct, add_struct_field, and modify_struct_field. The setting is read when the MCP server starts or restarts. Function/global convention warnings are still returned when enforcement is disabled.

Example: exposing to a private LAN with auth

export GHIDRA_MCP_AUTH_TOKEN=$(openssl rand -hex 32)
export GHIDRA_MCP_ALLOW_SCRIPTS=1     # only if your workflow needs it
export GHIDRA_MCP_FILE_ROOT=/srv/ghidra/inputs

# Headless server (`mvn clean package -P headless -DskipTests`). The jar does not
# bundle Ghidra, so Ghidra's Framework/Features/Processors jars go on the
# classpath too -- docker/entrypoint.sh builds exactly that command.
java -cp "target/GhidraMCP-<version>.jar:<ghidra jars>" \
  com.xebyte.headless.GhidraMCPHeadlessServer --bind 0.0.0.0 --port 8089

The headless server serves only its Unix domain socket unless --port or --bind is given; either one adds the TCP listener.

Ghidra Server authentication

When connecting to a shared Ghidra Server, GhidraMCP can suppress the password dialog automatically. It resolves credentials in this order (first non-empty value wins):

Compatibility note: Ghidra 12.1.4 clients require Ghidra Server 12.1.2, 12.0.5, or a newer compatible server. Older shared servers are not safe targets for a 12.1 client upgrade.

GHIDRA_SERVER_PASSWORD environment variable (or .env file in the Ghidra install directory or ~)
~/.ghidra-cred — single-line password file in your home directory
<ghidra-install-dir>/.ghidra-cred

Username resolves similarly: GHIDRA_SERVER_USER env var → user.name system property.

If no password is found, Ghidra shows its normal GUI prompt. Set these in .env (see .env.template for the full block) to enable silent auth.

Migration from v5.4.0 → v5.4.1

Script endpoints now default-off. If you relied on /run_script_inline or /run_ghidra_script, export GHIDRA_MCP_ALLOW_SCRIPTS=1. This is a deliberate breaking change; the prior default was unsafe.
Localhost-only deployments need no changes. Auth, bind refusal, and path-root checks are all opt-in.

❓ Troubleshooting

`spawn uv ENOENT` / `spawn python ENOENT` when the client starts the server

Cause: the MCP client could not find the command on its own PATH. This happens before any bridge code runs, so there is nothing in the Ghidra log or the bridge log to look at — the process was never created.

It shows up when the client is launched by something other than a login shell:

a systemd user service (systemctl --user), whose PATH is /usr/local/bin:/usr/bin:/bin unless you extend it;
a desktop .desktop entry, dock icon, or app launcher;
macOS apps started from Finder, which inherit launchd's PATH.

None of those contain ~/.local/bin (uv's default install location) or ~/.cargo/bin, so "command": "uv" cannot resolve even though uv works perfectly in your terminal.

Solution: use an absolute path in the client config.

// before — resolves against the client's PATH, fails under a service/GUI launcher
"command": "uv"
// after — no PATH lookup at all
"command": "/home/<you>/.local/bin/uv"

Find yours with which uv (POSIX) or where.exe uv (Windows). Or run:

python -m tools.setup preflight

which prints the resolved absolute path, the PATH entries it searched when a launcher is missing, and a ready-to-paste config snippet. Note what that check can and cannot tell you: it resolves against your shell's PATH, not the client's, so a pass there is evidence, not proof — the absolute path is what actually removes the failure mode. (#441)

If you must keep a bare command name, give the service manager the PATH instead — e.g. Environment="PATH=%h/.local/bin:/usr/local/bin:/usr/bin:/bin" in the unit file, or systemctl --user import-environment PATH — but the absolute path is the smaller and more portable fix.

"GhidraMCP" menu not appearing in Tools

Cause: Plugin not enabled or installed incorrectly.

Solution:

Verify extension is installed: File > Install Extensions — GhidraMCP should be listed
Enable the plugin: File > Configure > Utility > Configure > GhidraMCPPlugin (check the box)
Restart Ghidra after installation/enabling

Illustrated walkthrough: docs/INSTALL_GUI.md.

Server not responding / Connection refused

Cause: Server not started or wrong port.

Solution:

Check the server state: Tools > GhidraMCP > Server Status (it starts with the plugin; use Restart Server if it is stopped)
Check configured port: Edit > Tool Options > GhidraMCP HTTP Server

Check if port is in use:

# Linux/macOS
lsof -i :8089
# Windows
netstat -ano | findstr :8089

Look for errors in Ghidra console: Window > Console

`pip install` fails with `error: externally-managed-environment`

Cause: PEP 668. Debian-family distros (Debian 12+, Kali, Ubuntu 23.04+) mark the system Python as externally managed, so global pip install is blocked to protect apt-managed packages.

Solution: Use a virtual environment — never --break-system-packages. The recommended path is uv, which manages a project-local .venv automatically:

curl -LsSf https://astral.sh/uv/install.sh | sh
cd ghidra-mcp
uv run bridge-mcp-ghidra

Or a classic venv:

python3 -m venv .venv && source .venv/bin/activate
pip install -e .
bridge-mcp-ghidra

The `debugger_*` tools do not appear

Cause: The 22 bridge-side debugger proxies are off by default. They register only when GHIDRA_DEBUGGER_URL is set or GHIDRA_DEBUGGER_TOOLS=1, and they forward to an external debugger server that is not part of this repository.

Solution: start your debugger server, then set the URL before launching the bridge:

export GHIDRA_DEBUGGER_URL=http://127.0.0.1:8099

If the tools appear but every call reports that the server is not running, the URL is wrong or the server is down. GHIDRA_DEBUGGER_TOOLS=0 turns them off again even with a URL configured.

500 Internal Server Errors

Cause: Server-side exception, often due to missing program data.

Solution:

Ensure a binary is loaded in CodeBrowser
Run auto-analysis first: Analysis > Auto Analyze
Check Ghidra console (Window > Console) for Java exceptions
Some operations require fully analyzed binaries

404 Not Found Errors

Cause: Endpoint doesn't exist or wrong URL.

Solution:

Verify the endpoint exists: curl -s http://127.0.0.1:8089/mcp/schema lists every tool the server advertises
Check for typos in endpoint name
Ensure you're using correct HTTP method (GET vs POST)
If a script or prompt calls a tool that worked before 7.0.0 (decompile_function, list_functions, search_functions, get_function_callers, list_imports, ...), it was consolidated: the 7.0.0 migration guide names the replacement for every removed tool
Some routes exist on only one server: /debugger/* and /tool/* are GUI-only, and /create_project, /close_project, /delete_project and /list_projects are headless-only (see the API Reference)

Python Ghidra scripts fail with "No script provider found"

Cause: In Ghidra 12.1.4, Jython support is no longer enabled by default. .py scripts need the bundled Jython extension; Python 3 scripts should use PyGhidra instead of the Ghidra Script Manager.

Solution:

In the Ghidra Front End, open File > Install Extensions.
Check Jython, restart Ghidra, then refresh Script Manager.
For new automation, prefer Java Ghidra scripts or PyGhidra.

Extension not appearing in Install Extensions

Cause: JAR file in wrong location.

Solution:

Manual install location: ~/.config/ghidra/ghidra_12.1.4_PUBLIC/Extensions/GhidraMCP/lib/GhidraMCP.jar (%APPDATA%\ghidra\... on Windows, ~/Library/ghidra/... on macOS)
Or use: File > Install Extensions > Add and select the ZIP file — see the illustrated guide
Ensure JAR/ZIP was built for your Ghidra version

Build fails with "Ghidra dependencies not found"

Cause: Ghidra JARs not installed in local Maven repository (Maven backend only; Gradle reads them straight from the installation).

Solution:

# Windows (recommended)
python -m tools.setup install-ghidra-deps --ghidra-path "C:\ghidra_12.1.4_PUBLIC"

Under Gradle, a wall of package ghidra.program.model.address does not exist errors instead means -PGHIDRA_INSTALL_DIR resolved to nothing — in Git Bash, write the path with forward slashes.

📊 Production Performance

MCP Tools: 209 tools fully implemented (the whole catalog; the GUI plugin serves 205 of them and the headless server 190)
Speed: Sub-second response for most operations
Efficiency: 93% reduction in API calls via batch operations
Reliability: Atomic transactions with all-or-nothing semantics
AI Workflows: Proven documentation prompts refined across hundreds of real functions
Deployment: Automated version-aware deployment script

🛠️ API Reference

209 MCP tools backed by HTTP endpoints, grouped by catalog category. Generated from tests/endpoints.json by python -m tools.gen_readme_api_reference --write; the live schema at /mcp/schema is authoritative at runtime. Usage patterns: docs/prompts/TOOL_USAGE_GUIDE.md.

186 of these are served by both the GUI plugin and the standalone headless server. The rest are marked (GUI only) (19) or (headless only) (4) — calling one against the other server returns a 404, not an error message. See python -m tools.audit_server_scope for how the split is derived.

Program & Session Management

analysis_status - Get auto-analysis status for open programs
close_program - Close an open program by project path or name
create_memory_block - Create memory block, optionally initialized with byte contents (hex or base64)
create_property_map - Create a user property map to store typed values keyed by address
delete_bookmark - Delete bookmark
delete_property_map - Delete a user property map and all values it holds
exit_ghidra - Save and exit Ghidra
get_address_spaces - List all physical and overlay address spaces in the program (overlays include is_overlay flag and overlayed_space name)
get_language_metadata - Dump the program's language description: address spaces, registers, default symbols, endianness, pointer size (issue #192)
get_metadata - Get program metadata
get_program_options - Read all options in a program option group with types, current values, defaults, and descriptions
get_property - Read the value stored at an address in a property map
import_file - Import a binary file from disk into the current Ghidra project and open it
list_bookmarks - List bookmarks
list_open_programs - List open programs
list_project_files - List project files
list_properties - List (address, value) entries stored in a property map, with pagination
list_scripts - List available Ghidra scripts
open_program - Open program from project
read_memory - Read raw memory
reanalyze - Trigger full auto-analysis on a program
remove_program_option - Remove an option from a program option group
remove_property - Remove the value stored at a single address in a property map
run_ghidra_script - Run script with output capture
run_script_inline - Run inline script code
save_all_programs - Save all open programs
save_program - Save current program
set_bookmark - Set bookmark
set_image_base - Set the base address of the program (rebases all addresses)
set_memory_block - Change an existing memory block's permissions or volatility
set_program_option - Set a typed program option
set_property - Set a value at an address in a property map
switch_program - Switch current program

Project Organization

archive_project - Archive the currently open project to a Ghidra-native .gar file
create_folder - Create a folder in the project
delete_file - Delete a file from the project
delete_project - Delete a Ghidra project (headless only)
export_program - Export an open or project-resident program to a Ghidra Zip File (.gzf)
get_project_info - Get info about the currently open project
import_program - Import a Ghidra Zip File (.gzf) into the currently open project as a new DomainFile under target_folder (default '/')
list_projects - List available Ghidra projects (headless only)
move_file - Move a program file to a different folder in the project, preserving analysis and documentation
move_folder - Move a project folder and everything under it into another folder
restore_project - Restore a Ghidra .gar archive into a fresh on-disk project at parent_dir/project_name

Headless Project & Program Lifecycle

Available on the standalone headless server (GhidraMCPHeadlessServer).

close_project - Close the currently open project (headless only)
create_project - Create a new Ghidra project (headless only)
open_project - Open an existing Ghidra project (.gpr file or directory)

Listing & Enumeration

convert_number - Convert number between bases
find_functions - Find functions: every filter is optional, so with none it lists the whole program a page at a time
get_entry_points - Get program entry points
get_external_location - Get external location details
get_function_count - Return the number of functions in the loaded program
list_calling_conventions - List available calling conventions
list_data_items_by_xrefs - List data sorted by xref count
list_globals - List global variables
list_program_items - List one kind of program inventory with pagination
list_shadowed_globals - List named global DATA symbols that have NO type of their own because a larger data unit starting at an earlier address covers them
list_strings - List defined strings
search_strings - Search defined strings by a regex/substring pattern

Current GUI Context

get_ui_cursor - What the analyst is looking at right now: cursor address, the function under it, the listing selection, and the focused program — one call instead of four

Functions: Decompile, Rename, Prototypes & Variables

add_function_tag - Attach tags to ONE function (function + tags) OR MANY in one transaction (assignments=[{function,tags}, ...])
batch_rename_function_components - Batch rename function components
clear_flow_and_repair - Run Ghidra's GUI 'Clear Flow and Repair' action on a seed range: clears instruction flow reachable from the seed, then repairs function bodies and re-disassembles retained flow (ClearFlowAndRepairCmd with clear_data=false, clear_labels=false, repair=true)
clear_instruction_flow_override - Clear flow override
create_function - Create function at address
delete_function - Delete function at address
delete_function_tag - Delete a program-wide function tag definition
disassemble_bytes - Disassemble byte range
disassemble_function - Disassemble function
force_decompile - Force fresh decompilation
get_functions - Everything about one or many functions in a single call
list_class_members - List the member functions of a C++ class
list_function_tags - List all program-wide function tag definitions with their use counts
remove_function_tag - Detach one or more tags from a function
rename_function - Rename function by name
rename_variables - Batch rename variables
set_function_no_return - Set no-return attribute
set_function_prototype - Set function prototype (return type, param types, calling convention)
set_function_tag_comment - Update the comment/description on an existing program-wide function tag
set_function_this_type - Set the decompiler/database type of the implicit 'this' pointer (ECX on x86 __thiscall/__fastcall)
set_variable_storage - Set variable storage
set_variable_type - Set the data type of a function variable (local OR parameter) by name at the decompiler (high-level) layer
set_variables - Set types and names for multiple variables atomically

Symbols, Labels & Globals

can_rename_at_address - Check if address can be renamed
create_label - Create label
delete_label - Delete label at address
rename_symbol - Rename a symbol of any kind

Cross-References & Call Graphs

add_memory_reference - Create a user-defined cross-reference between two memory addresses that the auto-analyzer can't infer (runtime-populated pointer tables, vtables, late-bound function pointers, missed jump/switch tables)
analyze_call_graph - Analyze function call graph patterns
get_assembly_context - Get assembly context
get_full_call_graph - Get full call graph
get_function_call_graph - Get call graph
get_xrefs_from - Get references from address
get_xrefs_to - Get references to address
remove_reference - Remove memory cross-reference(s) from one address to another — the inverse of add_memory_reference

Data Types & Structures

add_struct_field - Add struct field
analyze_global_completeness - Score a global variable's documentation completeness on a budgeted 0-100 scale — the data-address analog of analyze_function_completeness
analyze_struct_field_usage - Analyze struct field usage
apply_data_classification - Apply data classification
apply_data_type - Apply data type
audit_global - Audit a global variable's documentation state
audit_globals_in_function - Audit every global variable referenced from within a function in one call
clone_data_type - Clone data type
create_data_type_category - Create data type category
create_derived_type - Create a type built on another: a typedef alias, an array or a pointer
create_enum - Create enumeration
create_function_signature - Create function signature type
create_struct - Create structure
create_union - Create union
delete_data_type - Delete data type
find_data_types - Find data types by name or path pattern, category and kind, one record per type (name, kind, category, size, path)
get_enum_values - Get enumeration values
get_struct_layout - Get structure layout
get_type_size - Get data type size and info
get_valid_data_types - Get valid data type names
import_data_types - Import data types from GDT
modify_struct_field - Modify a field in a structure: retype it (new_type, which also embeds a struct by value, e.g
move_data_type_to_category - Move data type to category
recreate_struct - Replace a structure in one step: optionally remove an existing same-named type, then create with fields JSON (same shape as create_struct)
remove_struct_field - Remove struct field
rename_data_type - Rename a data type (struct, union, enum, typedef) in place, preserving existing applications of it
resize_struct - Grow or shrink an existing structure by total byte size
resolve_duplicate_type - Find duplicate data types by simple name; delete unused /Demangler size-1 stubs when a larger canonical type exists
set_global - Atomically apply name + type + plate-comment + array length to a global variable
suggest_field_names - Suggest field names
validate_data_type - Validate data type syntax
validate_function_prototype - Validate function prototype

Comments

batch_set_comments - Set multiple comments
clear_function_comments - Clear all comments for a function
get_comment - Get listing comments (plate/pre/eol/post/repeatable) at ANY address, including data addresses (works on functions and data globals alike), for ONE address (address=) or MANY in one call (addresses=a,b,c)
set_comment - Set a listing comment of a given kind (plate/pre/eol/post/repeatable) at ANY address, including data addresses

Analysis

analyze_control_flow - Analyze control flow
analyze_data_region - Analyze data region
analyze_dataflow - Trace value propagation through a function (PCode graph, forward/backward)
analyze_for_documentation - Composite RE documentation analysis (decompile + classify + variables + completeness)
analyze_function_complete - Comprehensive single-call function analysis
analyze_function_completeness - Analyze documentation completeness
apply_documentation - Apply documentation to ONE function (fields at the top level) OR MANY (entries=[{address, ...}, ...])
configure_analyzer - Configure an analysis plugin
detect_array_bounds - Detect array bounds
find_code_gaps - Find gaps of undefined bytes between functions in executable memory
find_dead_code - Find dead code
find_next_undefined_function - Find next undefined function
find_similar_functions - Find similar functions
get_field_access_context - Get field access context
get_function_pcode - Dump raw P-code for a function (issue #192)
inspect_memory_content - Inspect memory bytes
list_analyzers - List available analysis plugins
run_analysis - Run auto-analysis on the current program
search_byte_patterns - Search for byte patterns
search_instructions - Search for instructions by mnemonic and/or operand substring

Malware & Anti-Analysis

analyze_api_call_chains - Analyze API call chains
detect_crypto_constants - Detect crypto constants
detect_malware_behaviors - Detect malware behaviors
extract_iocs_with_context - Extract IOCs with context
find_anti_analysis_techniques - Find anti-analysis techniques

Cross-Binary Documentation & Archive

archive_ingest_function - Ingest a single function's documentation into the cross-version archive (the doc archive service configured via GHIDRA_MCP_ARCHIVE_URL)
archive_ingest_program - Bulk-ingest every function in a program into the cross-version documentation archive
batch_string_anchor_report - Report of source file strings and their FUN_* functions
bulk_fuzzy_match - Bulk cross-binary function matching
compare_programs_documentation - Compare documentation across programs
diff_functions - Diff two functions
find_similar_functions_fuzzy - Cross-binary fuzzy function matching
find_undocumented_by_string - Find undocumented functions referencing string
get_function_documentation - Export function documentation
get_function_hash - Compute the normalized opcode hash of ONE function (function=), or of MANY in one call by omitting it: every function, paged, optionally only the documented or undocumented ones (filter=)
merge_program_documentation - Bulk merge: copy all RE documentation (function names, signatures, plate comments, instruction comments at EOL/PRE/POST, non-default labels & global symbols) from one program to another at matching addresses

Health, Schema & Tool Control

check_connection - Liveness probe: {status, server_kind (gui/headless), version, program when one is current}
mcp_health - Server health: kind (gui/headless), build, current program, uptime, HTTP pool, memory, endpoint count
mcp_schema - Machine-readable API schema with endpoint metadata
tool_goto_address - Navigate CodeBrowser listing and decompiler to a specific address (GUI only)
tool_running_tools - List all running Ghidra tool windows (GUI only)

Emulation

emulate_function - Emulate a single function with controlled register/memory inputs
emulate_hash_batch - Brute-force API hash resolution

Ghidra Server & Version Control

checkin_program - Check an open program back in to the shared Ghidra Server as a new version
server_admin_set_permissions - Set user permissions on a repository
server_admin_terminate_all_checkouts - Terminate all checkouts in a folder recursively
server_admin_terminate_checkout - Terminate all checkouts on a single file
server_admin_users - List all users on the server
server_authenticate - Register server credentials for programmatic authentication
server_checkouts - List all checked-out files in a folder, including server-side checkouts
server_connect - Report/establish the Ghidra server connection
server_disconnect - Disconnect from the Ghidra server
server_repositories - List repositories on the connected server
server_repository_create - Create a new repository on the server
server_repository_file - Get file info from a server repository
server_repository_files - List files in a server repository folder
server_status - Check headless server connection status
server_version_control_add - Add a file to version control
server_version_control_checkout - Check out a version-controlled file
server_version_control_undo_checkout - Undo a file checkout
server_version_history - Get version history for a file

Debugger (Ghidra TraceRmi)

When the bridge's opt-in WinDbg debugger proxies are enabled (GHIDRA_DEBUGGER_URL or GHIDRA_DEBUGGER_TOOLS=1), a TraceRmi tool below that shares a proxy's name gets a _2 suffix (e.g. debugger_status_2), so both stay reachable.

debugger_dynamic_to_static - Translate a runtime dynamic address from the current trace back to a static Ghidra program address (GUI only)
debugger_interrupt - Interrupt (break into) the running target (GUI only)
debugger_launch - Launch an executable through Ghidra's Trace RMI debugger launcher (GUI only)
debugger_launch_offers - List available debugger launch/attach options for the current program (GUI only)
debugger_list_breakpoints - List all breakpoints in the current trace (GUI only)
debugger_modules - List modules (DLLs/EXEs) loaded in the debugged process (GUI only)
debugger_read_memory - Read memory from the debugged process (GUI only)
debugger_registers - Read CPU registers from the current debug trace snapshot (GUI only)
debugger_remove_breakpoint - Remove a breakpoint at an address (GUI only)
debugger_resume - Resume execution of the debugged process (GUI only)
debugger_set_breakpoint - Set a software execution breakpoint at an address in the trace (GUI only)
debugger_stack_trace - Get the call stack backtrace for the current thread (GUI only)
debugger_static_to_dynamic - Translate a static Ghidra program address to a runtime dynamic address in the current trace (GUI only)
debugger_status - Get debugger status: active trace, thread, execution state, module count (GUI only)
debugger_step - Single-step the debugged process: into the next instruction (follows calls), over it (does not follow calls), or out of the current function (run to return) (GUI only)
debugger_traces - List all open debug traces (GUI only)

System

prompt_policy - Temporarily enable, disable, or query scoped automation prompt handling (GUI only)

Bridge Static Tools

Defined in the Python bridge itself (instance discovery, tool-group management); always available even before a Ghidra connection. The bridge can also proxy 22 debugger_* WinDbg tools to an external debugger server; they are off by default and register only when GHIDRA_DEBUGGER_URL is set or GHIDRA_DEBUGGER_TOOLS=1.

check_tools - Report which tools are currently registered and callable
connect_instance - Connect the bridge to a specific Ghidra instance
import_file - Import a binary from disk into the current project and open it
list_instances - Discover running Ghidra MCP instances (UDS + TCP port scan)
list_tool_groups - List tool groups and their load state
load_tool_group - Register a tool group's dynamic tools with the MCP client
search_tools - Search the full tool catalog by keyword
unload_tool_group - Unregister a tool group's dynamic tools

See CHANGELOG.md for version history.

🏗️ Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   AI/Automation │◄──►│   MCP Bridge    │◄──►│  Ghidra Plugin  │
│     Tools       │    │ (bridge_mcp_    │    │ (GhidraMCP.jar) │
│  (Claude, etc.) │    │  ghidra/)       │    │                 │
└─────────────────┘    └─────────────────┘    └─────────────────┘
        │                       │                       │
   MCP Protocol            HTTP REST              Ghidra API
(stdio/streamable-http) (localhost:8089)      (Program, Listing)

Components

python/bridge_mcp_ghidra/ — Python MCP server package (ships as the ghidra-mcp-bridge wheel; bridge-mcp-ghidra console script) that translates MCP protocol to HTTP calls (209 catalog entries)
GhidraMCP.jar — Ghidra plugin that exposes analysis capabilities via HTTP (205 endpoints)
GhidraMCPHeadlessServer — Standalone headless server — 190 endpoints, no GUI required
ghidra_scripts/ — Collection of automation scripts for common tasks

🔧 Development

Building from Source

# Recommended: direct Python-first workflow
python -m tools.setup ensure-prereqs --ghidra-path "C:\ghidra_12.1.4_PUBLIC"
python -m tools.setup build
python -m tools.setup deploy --ghidra-path "C:\ghidra_12.1.4_PUBLIC"

# Version bump (updates all maintained version references atomically)
python -m tools.setup bump-version --new X.Y.Z

Both Java backends are maintained. Gradle (./gradlew, wrapper committed) is the default for local work and writes to build/; CI builds and gates with Maven, which writes to target/. tools.setup routes through Maven unless TOOLS_SETUP_BACKEND=gradle. Three things exist only under Maven: regenerating tests/endpoints.json (mvn test -Dtest=RegenerateEndpointsJson -Dregenerate=true), the JaCoCo coverage gate, and the headless/docker build profiles.

Command Reference

Command	What it does
`ensure-prereqs`	Install Python deps + Ghidra Maven JARs in one shot. Start here on a new machine.
`preflight`	Validate Python, build tool, Ghidra path, and JAR availability without making changes. Add `--strict` to also check network reachability.
`build`	Build the plugin JAR and extension ZIP via Maven (or Gradle when `TOOLS_SETUP_BACKEND=gradle`).
`deploy`	Copy the built extension into the Ghidra profile and patch `FrontEndTool.xml` for auto-activation.
`start-ghidra`	Launch the configured Ghidra installation.
`clean`	Remove the selected backend's build output (`target/`, or `build/` under Gradle).
`clean-all`	Remove build outputs plus local cache artifacts (`.m2` Ghidra JARs, etc.).
`install-ghidra-deps`	Install only the Ghidra JARs into `~/.m2`. Useful when the build environment changes.
`install-python-deps`	Install the Python dependency groups via `uv sync`.
`run-tests`	Run the backend's whole Java `test` task (`mvn test`, or `gradlew test` under Gradle). The integration classes in it need a live Ghidra on port 8089.
`verify-version`	Check `pom.xml`'s Ghidra version against the `--ghidra-path` installation (same major.minor series passes).
`bump-version --new X.Y.Z`	Atomically update all version references. Pass `--tag` to create a git tag.

Common flags accepted by most commands:

Flag	Description
`--ghidra-path PATH`	Ghidra installation directory. Defaults to `GHIDRA_PATH` from `.env`.
`--dry-run`	Print actions without executing them.
`--force`	Reinstall Ghidra JARs even if already present (`install-ghidra-deps`, `ensure-prereqs`).
`--with-debugger`	Force-install debugger Python requirements (Windows only).
`--use-debugger-toggle`	Read `INSTALL_DEBUGGER_DEPS` from `.env` to decide whether to install debugger deps.
`--test TIER`	(`deploy` only) Opt into live deploy regression tiers such as `release` or `debugger-live`.
`--strict`	(`preflight` only) Also check network reachability for Maven Central and PyPI.

Deploy test tiers are opt-in because benchmark tiers can import/reset Benchmark.dll and BenchmarkDebug.exe in the active Ghidra project. Use --test release before cutting releases, or set GHIDRA_MCP_DEPLOY_TESTS=release in a local .env when you want every deploy on your machine to run the live benchmark regression. The value is validated against the same tier list --test accepts, and an unknown tier is refused rather than skipped. See Testing and Release Regression.

# Standard first-time setup and deploy
python -m tools.setup ensure-prereqs --ghidra-path "C:\ghidra_12.1.4_PUBLIC"
python -m tools.setup build
python -m tools.setup deploy --ghidra-path "C:\ghidra_12.1.4_PUBLIC"

# Preflight check before deploying
python -m tools.setup preflight --strict --ghidra-path "C:\ghidra_12.1.4_PUBLIC"

# Version bump and tag
python -m tools.setup bump-version --new X.Y.Z --tag

# Run the Java test suite (integration classes need a live Ghidra)
python -m tools.setup run-tests

# Show full help
python -m tools.setup --help

Project Structure

ghidra-mcp/
├── pyproject.toml           # uv project (ghidra-mcp-bridge wheel + dependency groups)
├── python/bridge_mcp_ghidra/ # MCP server package (Python, 209 catalog entries)
├── src/main/java/           # Ghidra plugin + headless server (Java)
│   └── com/xebyte/
│       ├── GhidraMCPPlugin.java         # GUI plugin (205 endpoints)
│       ├── headless/                    # Headless server (190 endpoints)
│       └── core/                        # Shared service layer (`*Service.java`, `@McpTool`-annotated)
├── ghidra_scripts/          # Automation scripts for batch workflows
├── tests/                   # Python unit tests + endpoint catalog
│   ├── unit/               # Catalog consistency, schema, tool function tests
│   └── endpoints.json      # Endpoint catalog (the authoritative tool list)
├── docs/                    # Documentation
│   ├── prompts/            # AI workflow prompts (V5 documentation workflows)
│   ├── releases/           # Version release notes
│   └── project-management/ # Contributor planning docs (Gradle migration, etc.)
├── tools/setup/             # Build and deployment CLI (python -m tools.setup)
├── docker/                  # Headless server + bridge containers
└── .github/workflows/      # CI/CD pipelines

Library Dependencies

Under the Maven backend, Ghidra JARs must be installed into your local Maven repository (~/.m2/repository) before compilation. This is a one-time setup per machine, and again when your Ghidra version changes. ensure-prereqs does it for you; Gradle needs no such step, because it reads the jars from the installation.

The tool enforces version consistency between:

pom.xml (ghidra.version)
--ghidra-path version segment (e.g., ghidra_12.1.4_PUBLIC)

If they are not in the same major.minor series, deployment fails fast with a clear error (a different patch release of the same series is accepted).

Troubleshooting: Version Mismatch

If you see a version mismatch error, align both values:

pom.xml → ghidra.version
--ghidra-path version segment (ghidra_X.Y.Z_PUBLIC)

Then rerun:

python -m tools.setup preflight --ghidra-path "C:\ghidra_12.1.4_PUBLIC"

# Windows
python -m tools.setup install-ghidra-deps --ghidra-path "C:\path\to\ghidra_12.1.4_PUBLIC"

Required Libraries (18 JARs, as listed in tools/setup/ghidra.py):

Library	Source Path	Purpose
Base.jar	`Features/Base/lib/`	Core Ghidra functionality
Decompiler.jar	`Features/Decompiler/lib/`	Decompilation engine
PDB.jar	`Features/PDB/lib/`	Microsoft PDB symbol support
FunctionID.jar	`Features/FunctionID/lib/`	Function identification
SoftwareModeling.jar	`Framework/SoftwareModeling/lib/`	Program model API
Project.jar	`Framework/Project/lib/`	Project management
Docking.jar	`Framework/Docking/lib/`	UI docking framework
Generic.jar	`Framework/Generic/lib/`	Generic utilities
Utility.jar	`Framework/Utility/lib/`	Core utilities
Gui.jar	`Framework/Gui/lib/`	GUI components
FileSystem.jar	`Framework/FileSystem/lib/`	File system support
Graph.jar	`Framework/Graph/lib/`	Graph/call graph analysis
DB.jar	`Framework/DB/lib/`	Database operations
Emulation.jar	`Framework/Emulation/lib/`	P-code emulation
Help.jar	`Framework/Help/lib/`	Help system
Debugger-api.jar	`Debug/Debugger-api/lib/`	Debugger service API
Framework-TraceModeling.jar	`Debug/Framework-TraceModeling/lib/`	Debug trace model
Debugger-rmi-trace.jar	`Debug/Debugger-rmi-trace/lib/`	Trace RMI debugger connection

Note: Libraries are NOT included in the repository (see .gitignore). You must install them from your Ghidra installation before building.

Automation entry point:

python -m tools.setup is the supported setup/build/deploy/versioning interface

use ensure-prereqs, build, deploy, preflight, clean-all, and bump-version directly

these commands use Maven unless TOOLS_SETUP_BACKEND=gradle is set

Development Features

Automated Deployment: Version-aware deployment script
Batch Operations: Reduces API calls by 93%
Atomic Transactions: All-or-nothing semantics
Comprehensive Logging: Debug and trace capabilities

📚 Documentation

Core Documentation

Documentation Index - Complete documentation navigation
Project Structure - Project organization guide
Testing and Release Regression - Local tests, CI, live Ghidra regression, and release gates
Naming Conventions - Code naming standards
Hungarian Notation - Variable naming guide

AI Workflow Prompts

Function Documentation V5 — Primary workflow: 7-step process with Hungarian notation, type auditing, and verification scoring
Batch Documentation V5 — Parallel subagent dispatch for multi-function processing
Orphaned Code Discovery — Automated scanner for undiscovered functions
Data Type Investigation — Structure discovery and field analysis
Global Data Analysis — Global naming and analysis
Quick Start Prompt — Simplified beginner workflow
All Prompts — Complete prompt index

Release History

Complete Changelog - All version release notes
Release Notes - Detailed release documentation

🐳 Headless Server (Docker)

GhidraMCP includes a headless server mode for automated analysis without the Ghidra GUI.

Quick Start with Docker

# Build and run (the compose files live in docker/). The token is required:
# the container binds 0.0.0.0, and the server refuses a non-loopback bind
# without one.
cd docker
export GHIDRA_MCP_AUTH_TOKEN=$(openssl rand -hex 32)
docker compose up -d --build

# Test connection (/check_connection and /mcp/health need no token)
curl http://localhost:8089/check_connection
# {"status": "ok", "server_kind": "headless", "version": "7.0.0"}

This starts the headless server on :8089 and the MCP bridge on :8081 (streamable-http at /mcp). See docker/README.md for the full deployment guide.

Headless API Workflow

AUTH="Authorization: Bearer $GHIDRA_MCP_AUTH_TOKEN"

# 1. Import a binary into the open project (auto-analysis runs by default)
curl -X POST -H "$AUTH" -H 'Content-Type: application/json' \
     -d '{"file_path": "/data/program.exe"}' http://localhost:8089/import_file

# 2. Re-run auto-analysis later if needed
curl -X POST -H "$AUTH" http://localhost:8089/run_analysis

# 3. List discovered functions
curl -H "$AUTH" "http://localhost:8089/find_functions?limit=20"

# 4. Decompile a function
curl -H "$AUTH" "http://localhost:8089/get_functions?function=0x401000&fields=decompiled_code"

# 5. Get metadata
curl -H "$AUTH" http://localhost:8089/get_metadata

Key Headless Endpoints

Endpoint	Method	Description
`/import_file`	POST	Import a binary into the project and open it
`/open_program`	POST	Open a program already in the project (any `program=` also opens on demand)
`/run_analysis`	POST	Run Ghidra auto-analysis
`/find_functions`	GET	List or filter discovered functions
`/list_program_items`	GET	`kind=imports`, `exports`, `segments`, `classes`, `namespaces`, `data_items` or `external_locations`
`/get_functions`	GET	Decompiled code, signature, callers, callees and more for one or many functions (`fields=` picks)
`/create_function`	POST	Create function at address
`/get_metadata`	GET	Get program metadata
`/create_project`	POST	Create a Ghidra project (headless only)
`/list_analyzers`	GET	List available analyzers
`/server/status`	GET	Check Ghidra Server connection

Configuration

Environment variables for Docker:

GHIDRA_MCP_AUTH_TOKEN - Bearer token, required by the compose files (see above)
GHIDRA_MCP_PORT - Server port (default: 8089)
GHIDRA_MCP_BIND_ADDRESS - Bind address (default: 0.0.0.0 in Docker)
JAVA_OPTS - JVM options (default: -Xmx4g -XX:+UseG1GC)

🤝 Contributing

See CONTRIBUTING.md for detailed contribution guidelines.

Quick Start

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Build and test your changes (./gradlew buildExtension -PGHIDRA_INSTALL_DIR=/path/to/ghidra, or mvn clean package assembly:single -DskipTests under the Maven backend)
Update documentation as needed
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🏆 Production Status

Metric	Value
Version	7.0.0
MCP Tools	209 fully implemented
GUI Endpoints	205 (GhidraMCPPlugin)
Headless Endpoints	190 (GhidraMCPHeadlessServer)
Compilation	✅ 100% success
Batch Efficiency	93% API call reduction
AI Workflows	7 proven documentation workflows
Ghidra Scripts	Automation scripts included
Documentation	Comprehensive with AI prompts

See CHANGELOG.md for version history and release notes.

🙏 Acknowledgments

This project was originally derived from LaurieWired/GhidraMCP in August 2025 and has since been substantially rewritten and extended. We acknowledge LaurieWired's original work as the starting point. See NOTICE for license attribution.

Powered by

Tooling provided by JetBrains through their Open Source Support Program.

👥 Contributors

This project has benefited from the work of dedicated contributors:

Core Contributors

@heeen — Significant contributions including:

Fuzzy function matching and structured diff for cross-binary comparison (#13)
Script execution improvements and bug fixes (#12)
New API endpoints: save_program, exit_ghidra, delete_function, create_memory_block, run_script_inline (#11)
Architectural vision: annotation-driven design, UDS transport, Python bridge optimization proposals

@huehuehuehueing — Significant contributions including:

Address-space prefix support — added <space>:<hex> syntax (e.g., mem:1000, code:ff00) to address parsing across the entire endpoint surface, unlocking multi-space targets like embedded firmware (#84, closes #65)
Optional program parameter + required-param schema fixes — made program optional on every endpoint with a sane currentProgram fallback, and fixed several required-vs-optional schema bugs the catalog had inherited (#92)
Seeded #44 (data-type / enum tools) — the issue that motivated the v5.0 enum + struct enforcement layer
Ghidra Team - For the incredible reverse engineering platform
Model Context Protocol - For the standardized AI integration framework
Contributors - For testing, feedback, and improvements

🔗 Related Projects

re-universe — Ghidra BSim PostgreSQL platform for large-scale binary similarity analysis. Pairs perfectly with GhidraMCP for AI-driven reverse engineering workflows.
cheat-engine-server-python — MCP server for dynamic memory analysis and debugging.

Ready for production deployment with enterprise-grade reliability and comprehensive binary analysis capabilities.

Name		Name	Last commit message	Last commit date
.github		.github
.vscode		.vscode
docker		docker
docs		docs
ghidra_scripts		ghidra_scripts
gradle/wrapper		gradle/wrapper
lib		lib
python/bridge_mcp_ghidra		python/bridge_mcp_ghidra
src		src
tests		tests
tools		tools
.editorconfig		.editorconfig
.env.template		.env.template
.gitignore		.gitignore
.markdownlint-cli2.jsonc		.markdownlint-cli2.jsonc
.mcp.json.example		.mcp.json.example
AGENTS.md		AGENTS.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
NOTICE		NOTICE
README.md		README.md
ROADMAP.md		ROADMAP.md
SECURITY.md		SECURITY.md
build.gradle		build.gradle
ghidra-mcp-setup.ps1		ghidra-mcp-setup.ps1
gradlew		gradlew
gradlew.bat		gradlew.bat
pom.xml		pom.xml
pyproject.toml		pyproject.toml
settings.gradle		settings.gradle
uv.lock		uv.lock

Latest commit

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Repository files navigation

Ghidra MCP Server

Why Ghidra MCP?

Convention Enforcement

🌟 Features

Core MCP Integration

Binary Analysis Capabilities

Dynamic Analysis (v5.4.0)

AI-Powered Reverse Engineering Workflows

Development & Automation

🚀 Quick Start

Prerequisites

Installation

Installation (Linux — Ubuntu/Debian)

Installation (macOS — Homebrew)

Installation (Arch Linux — AUR)

Basic Usage

Option 1: Stdio Transport (Recommended for AI tools)

Option 2: Streamable HTTP Transport (Recommended for web/HTTP clients)

Option 3: SSE Transport (Deprecated — use streamable-http instead)

Bridge advanced flags

Lazy tool loading is the default (issue #440)

Strict program routing (multi-program safety)

Reducing tool-context overhead

Minimal read-only allowlist

Optional: Connect an external debugger server

In Ghidra

Verify It's Working

Support This Project

🔒 Security

Example: exposing to a private LAN with auth

Ghidra Server authentication

Migration from v5.4.0 → v5.4.1

❓ Troubleshooting

spawn uv ENOENT / spawn python ENOENT when the client starts the server

"GhidraMCP" menu not appearing in Tools

Server not responding / Connection refused

pip install fails with error: externally-managed-environment

The debugger_* tools do not appear

500 Internal Server Errors

404 Not Found Errors

Python Ghidra scripts fail with "No script provider found"

Extension not appearing in Install Extensions

Build fails with "Ghidra dependencies not found"

📊 Production Performance

🛠️ API Reference

Program & Session Management

Project Organization

Headless Project & Program Lifecycle

Listing & Enumeration

Current GUI Context

Functions: Decompile, Rename, Prototypes & Variables

Symbols, Labels & Globals

Cross-References & Call Graphs

Data Types & Structures

Comments

Analysis

Malware & Anti-Analysis

Cross-Binary Documentation & Archive

Health, Schema & Tool Control

Emulation

Ghidra Server & Version Control

Debugger (Ghidra TraceRmi)

System

Bridge Static Tools

🏗️ Architecture

Components

🔧 Development

Building from Source

Command Reference

Project Structure

Library Dependencies

Troubleshooting: Version Mismatch

Development Features

📚 Documentation

Core Documentation

AI Workflow Prompts

`spawn uv ENOENT` / `spawn python ENOENT` when the client starts the server

`pip install` fails with `error: externally-managed-environment`

The `debugger_*` tools do not appear