mcp.llamaindex.ai

An authenticated Model Context Protocol (MCP) server that exposes LlamaParse document processing capabilities to any MCP-compatible AI client. Built with Next.js 15 and deployed on Vercel, it uses WorkOS AuthKit for OAuth authentication so users sign in with their LlamaCloud credentials (no API key sharing required).

MCP Tools

Tool	Description
getUploadUrl	Returns a short-lived pre-signed upload URL (and a browser upload link) for sending a file to LlamaParse storage
uploadFileByUrl	Uploads a file directly from a remote URL into LlamaParse storage
getUserProjects	Lists all LlamaCloud project IDs associated with the authenticated user
parseFile	Parses an uploaded file and returns its content as markdown or plain text
classifyFile	Classifies a file against a set of custom categories, returning the matched category, confidence score, and reasoning
splitFile	Splits a multi-section document into labelled segments based on custom categories

Architecture

MCP Client (Claude, Cursor, etc.)
        │  HTTP + OAuth token
        ▼
┌──────────────────────────────┐
│  Next.js App (Vercel)        │
│  /mcp  ──► @vercel/mcp-adapter│
│            │                 │
│            ▼                 │
│  WorkOS JWT verification     │
│  Rate limiter (in-memory)    │
│            │                 │
│            ▼                 │
│  LlamaParse tools            │
│  (@llamaindex/llama-cloud)   │
└──────────────────────────────┘
        │
        ▼  (getUploadUrl only)
┌───────────────┐
│  Redis KV     │  stores short-lived upload tokens (10 min TTL)
└───────────────┘

Using the hosted version

A production instance is already running at https://mcp.llamaindex.ai/mcp. You can connect any MCP-compatible client directly — no server setup required.

Claude Desktop

Add the following to your claude_desktop_config.json (typically at ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "llamaparse": {
      "type": "http",
      "url": "https://mcp.llamaindex.ai/mcp"
    }
  }
}

Restart Claude Desktop. On first use, open the MCP panel (/mcp slash command), select llamaparse, and click Re-authenticate to sign in with your LlamaCloud account.

Claude CLI

claude mcp add --transport http llamaparse https://mcp.llamaindex.ai/mcp

Then run /mcp inside a Claude session, click llamaparse → Re-authenticate, and complete the OAuth flow in your browser.

GitHub Copilot (VS Code)

Open your VS Code settings.json (Cmd/Ctrl+Shift+P → Open User Settings (JSON)) and add:

{
  "mcp": {
    "servers": {
      "llamaparse": {
        "type": "http",
        "url": "https://mcp.llamaindex.ai/mcp"
      }
    }
  }
}

Restart VS Code. Copilot will prompt you to authenticate the first time a LlamaParse tool is invoked in agent mode.

Cursor

Open Settings → MCP (or edit ~/.cursor/mcp.json) and add:

{
  "mcpServers": {
    "llamaparse": {
      "type": "http",
      "url": "https://mcp.llamaindex.ai/mcp"
    }
  }
}

Restart Cursor. The LlamaParse tools will appear in the Composer tool list. Cursor will redirect you to authenticate on first use.

---

Quickstart (local development)

Prerequisites

• Node.js 20+, pnpm 10+
• A WorkOS account with an AuthKit application
• A LlamaCloud account
• A Redis instance (local or cloud — required for file upload token storage)

1. Clone and install

git clone https://github.com/run-llama/mcp-llamaindex-ai
cd mcp-llamaindex-ai
pnpm install

2. Configure environment variables

Copy the example below into a .env.local file and fill in your values:

# WorkOS AuthKit
WORKOS_API_KEY=sk_...
WORKOS_CLIENT_ID=client_...
WORKOS_COOKIE_PASSWORD=<random-32-char-secret>   # used to sign session cookies
WORKOS_AUTHKIT_DOMAIN=https://<your-authkit-domain>.authkit.app
NEXT_PUBLIC_WORKOS_REDIRECT_URI=http://localhost:3000/callback

# Public URL of this deployment (no trailing slash)
# Use http://localhost:3000 for local dev
NEXT_PUBLIC_VERCEL_PROJECT_PRODUCTION_URL=http://localhost:3000

# LlamaCloud (optional — overrides the default API base)
LLAMA_CLOUD_BASE_URL=https://api.cloud.llamaindex.ai

# Redis — required for the pre-signed upload URL feature
REDIS_URI=redis://localhost:6379

WorkOS setup tip: In your WorkOS dashboard, add http://localhost:3000/callback as an allowed redirect URI for local development.

3. Run the dev server

pnpm dev

4. Connect an MCP client

Claude Desktop / Claude CLI:

claude mcp add --transport http llamaparse http://localhost:3000/mcp

Then open Claude, run /mcp, select llamaparse, and click Re-authenticate to complete the OAuth flow.

Cursor or other HTTP-transport clients: point them at http://localhost:3000/mcp.

Deploying to Vercel

After deployment, set the same environment variables in your Vercel project settings, updating NEXT_PUBLIC_VERCEL_PROJECT_PRODUCTION_URL and NEXT_PUBLIC_WORKOS_REDIRECT_URI to your production URL.

Connect your MCP client to the production endpoint:

claude mcp add --transport http llamaparse https://<your-deployment>.vercel.app/mcp

Development

pnpm dev          # start Next.js dev server
pnpm test         # run Jest test suite
pnpm test:watch   # watch mode
pnpm lint         # ESLint
pnpm prettier     # check formatting
pnpm prettier:fix # auto-fix formatting

License

MIT