# 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)
```
