Heavy backend for Claude Skills MCP server with vector search (Streamable HTTP)
Project description
Claude Skills MCP Backend
Heavy backend server for Claude Skills MCP system with vector search capabilities.
Overview
This is the backend component of the Claude Skills MCP system. It provides:
- Vector-based semantic search using sentence-transformers
- Skill indexing and retrieval
- MCP protocol via Streamable HTTP transport
- Background skill loading from GitHub and local sources
Note: This package is typically auto-installed by the frontend (claude-skills-mcp). You only need to install it manually for:
- Remote deployment (hosting your own backend)
- Development and testing
- Standalone usage without the frontend proxy
Installation
# Via uv (recommended)
uv tool install claude-skills-mcp-backend
# Via uvx (one-time use)
uvx claude-skills-mcp-backend
# Via pip
pip install claude-skills-mcp-backend
Usage
Run Standalone Server
# Default (localhost:8765)
claude-skills-mcp-backend
# Custom port
claude-skills-mcp-backend --port 8080
# For remote access
claude-skills-mcp-backend --host 0.0.0.0 --port 8080
# With custom configuration
claude-skills-mcp-backend --config my-config.json
# Verbose logging
claude-skills-mcp-backend --verbose
Configuration
# Print example configuration
claude-skills-mcp-backend --example-config > config.json
# Edit config.json to customize skill sources, embedding model, etc.
# Run with custom config
claude-skills-mcp-backend --config config.json
Endpoints
When running, the backend exposes:
- Streamable HTTP MCP:
http://localhost:8765/mcp - Health Check:
http://localhost:8765/health
Docker Deployment
Build Image
docker build -t claude-skills-mcp-backend .
Run Container
# For local access
docker run -p 8765:8765 claude-skills-mcp-backend
# For remote access
docker run -p 8080:8765 \
-e HOST=0.0.0.0 \
claude-skills-mcp-backend --host 0.0.0.0 --port 8765
Dependencies
This package includes heavy dependencies (~250 MB):
- PyTorch (CPU-only on Linux): ~150-200 MB
- sentence-transformers: ~50 MB
- numpy, httpx, fastapi, uvicorn: ~30 MB
First download may take 60-180 seconds depending on your internet connection.
Performance
- Startup time: 2-5 seconds (with cached dependencies)
- First search: +2-5 seconds (embedding model download, one-time)
- Query time: <1 second after models loaded
- Memory usage: ~500 MB
Development
# Clone the monorepo
git clone https://github.com/K-Dense-AI/claude-skills-mcp.git
cd claude-skills-mcp/packages/backend
# Install in development mode
uv pip install -e ".[test]"
# Run tests
uv run pytest tests/
Related Packages
- claude-skills-mcp (Frontend): Lightweight proxy that auto-installs this backend
- Main Repository: https://github.com/K-Dense-AI/claude-skills-mcp
License
Apache License 2.0
Copyright 2025 K-Dense AI (https://k-dense.ai)
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