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.

Related MCP server: Mono Memory MCP

Configuration

Copy .env.example to .env and adjust as needed:

MCP_HOST=0.0.0.0
MCP_PORT=9001

Run

uv run main.py

Local Verification

Use FastMCP CLI to verify the server without starting it:

# 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.

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.

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).