Generix

Custom MCP server that provides semantic search over documents in the docs/ folder. Uses ChromaDB for vector storage and OpenAI embeddings.

Setup

1. Clone this repo
2. Create a virtual environment and install dependencies:

   cd mcp_generix
   python3 -m venv .venv
   source .venv/bin/activate
   pip install "mcp[cli]" chromadb openai
   

3. Set your OpenAI API key:

   export OPENAI_API_KEY="your-key-here"
   

4. Add the MCP server to Claude Code:

   claude mcp add generix-docs -- /path/to/mcp_generix/.venv/bin/python /path/to/mcp_generix/server.py
   

Adding / Removing Documents

1. Add markdown (.md) or text files to the docs/ folder
2. Commit and push
3. Other team members pull to get the latest documents
4. The server re-indexes documents automatically on startup, or use the reindex_docs tool

Available Tools

Tool	Description
search_docs	Semantic search — find relevant passages by meaning, not just keywords
list_docs	List all documents in the docs folder
read_doc	Read the full contents of a specific document
reindex_docs	Re-index documents after adding/removing files

Folder Structure

mcp_generix/
├── server.py          ← MCP server with semantic search
├── pyproject.toml     ← Python dependencies
├── docs/              ← Shared documentation (managed via git)
│   └── (your documents here)
├── .chroma/           ← ChromaDB vector store (gitignored, local)
└── .venv/             ← Python virtual environment (gitignored, local)