HushClaw

Lightweight, token-first AI Agent framework with persistent memory and a built-in browser UI. Zero mandatory dependencies — pure Python stdlib.

Features

• Browser UI — full chat interface served at http://localhost:8765; sessions, memories, and multi-agent management panels; setup wizard on first launch
• Token-first design — explicit token budget per context section; Anthropic KV-cache support for the stable prefix
• Persistent memory — notes survive across sessions via SQLite FTS5 + local vector search
• Zero hard dependencies — runs with Python 3.11+ stdlib only (sqlite3, tomllib, asyncio, urllib)
• Multiple providers — Anthropic (urllib or SDK), Ollama, OpenAI-compatible
• ReAct loop — tool use with pluggable ContextEngine for lossless compaction
• Plugin tools — drop .py files into ~/.config/hushclaw/tools/ to extend
• Multi-agent — sequential pipelines, session-affinity pools, agent-to-agent delegation
• Native storage paths — macOS ~/Library/Application Support/hushclaw/, Linux ~/.local/share/hushclaw/

Install

macOS / Linux

bash <(curl -fsSL https://raw.githubusercontent.com/CNTWDev/hushclaw/master/install.sh)

Windows

Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
Invoke-WebRequest -Uri https://raw.githubusercontent.com/CNTWDev/hushclaw/master/install.ps1 -OutFile install.ps1
.\install.ps1

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hushclaw-web

The official skill directory for HushClaw — browse, discover, and rate community skills.

Tech Stack

• Backend: FastAPI + Uvicorn
• Database: SQLite + SQLAlchemy
• Templates: Jinja2
• Python: 3.11+

Project Structure

hushclaw-web/
├── app/
│   ├── main.py          # App entry point
│   ├── database.py      # DB connection
│   ├── models.py        # SQLAlchemy models
│   └── routes/
│       ├── home.py      # Home page
│       ├── skills.py    # Skills listing & detail
│       └── admin.py     # Admin panel
├── static/              # CSS, JS, images
├── requirements.txt
├── seed_data.py         # Seed initial data
└── start.sh             # Local dev startup script

Local Development (Mac)

./start.sh

Automatically creates a virtual environment, installs dependencies, and starts the server at http://localhost:8000.

Or manually:

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload --port 8000

Seed Data

source .venv/bin/activate
python seed_data.py

Data Models

• Category — skill categories with icon and slug
• Skill — title, description, platform, tags, ratings
• Rating — per-IP ratings (1 vote per user per skill)