# MCP Generix — Shared Documentation with Semantic Search

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:
   ```bash
   cd mcp_generix
   python3 -m venv .venv
   source .venv/bin/activate
   pip install "mcp[cli]" chromadb openai
   ```
3. Set your OpenAI API key:
   ```bash
   export OPENAI_API_KEY="your-key-here"
   ```
4. Add the MCP server to Claude Code:
   ```bash
   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)
```