mcp-hub

# mcp-hub A self-hosted remote MCP server that provides reusable prompts and conventions across AI tools. ## Structure ``` modules/ └── dev/ └── python.py # Python/uv conventions → prompt: dev_python_uv ``` Each domain is a subfolder under `modules/`. Each file exposes a `router` (a `FastMCP` instance) that gets mounted in `main.py`. ## Configuration Copy `.env.example` to `.env` and adjust as needed: ``` MCP_HOST=0.0.0.0 MCP_PORT=9001 ``` ## Run ```bash uv run main.py ``` ## Local Verification Use FastMCP CLI to verify the server without starting it: ```bash # List all registered tools uv run fastmcp list main.py # List tools + prompts uv run fastmcp list main.py --prompts # Inspect server details (JSON report) uv run fastmcp inspect main.py # Launch MCP Inspector (interactive browser UI for testing tools/prompts) uv run fastmcp dev inspector main.py ``` ## Connect Add as an MCP server in your AI tool using: - **Transport:** Streamable HTTP - **URL:** `http://<host>:<port>/mcp` ## Deploy on Linux **Option 1 — screen (recommended):** lets you detach and reattach to the session anytime. ```bash screen -S mcp-hub uv run main.py # Ctrl+A then D to detach # Reattach later: screen -r mcp-hub ``` **Option 2 — nohup:** fire-and-forget, no reattach. ```bash nohup uv run main.py > mcp-hub.log 2>&1 & # stop later pkill -f "mcp-hub" ``` ## Add a new module 1. Create `modules/<domain>/<topic>.py` with a `router = FastMCP(...)` and `@router.prompt` functions 2. Mount it in `main.py`: `mcp.mount(router, namespace="<domain>")` Prompts are namespaced as `<namespace>_<prompt_name>` (e.g. `dev_python_uv`).