MCP server/ai-tools

MCP Hub MCP Server

A self-hosted remote MCP server that provides reusable prompts and conventions

shanezchang/mcp-hub ↗by shanezchangupdated
1

Add it to Claude Code

claude mcp add mcp-hub -- uv run main.py
2

Make your agent remember this setup

mcp-hub's config, env vars, and the gotchas you hit — recalled in every future Claude Code, Cursor, and Codex session.

npx conare@latest

Free · one command · indexes the sessions already on disk. Set up in the browser instead →

What it does

  • Provides reusable prompts and development conventions
  • Modular architecture for organizing prompts by domain
  • Namespacing support for custom prompts
  • Remote-capable server via Streamable HTTP
  • Easy integration with AI tools as an MCP server

Environment Variables

MCP_HOSTThe host address for the MCP server
MCP_PORTThe port for the MCP server

Try it

Use the dev_python_uv prompt to set up my new Python project environment.
Apply the standard development conventions for my current module.
List all available prompts registered in the MCP Hub.
Original README from shanezchang/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

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>:/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>_ (e.g. dev_python_uv).

Frequently Asked Questions

What are the key features of MCP Hub?

Provides reusable prompts and development conventions. Modular architecture for organizing prompts by domain. Namespacing support for custom prompts. Remote-capable server via Streamable HTTP. Easy integration with AI tools as an MCP server.

What can I use MCP Hub for?

Standardizing coding conventions across a team's AI-assisted workflows. Managing domain-specific prompts for different programming languages. Centralizing reusable AI prompts in a self-hosted environment.

How do I install MCP Hub?

Install MCP Hub by running: uv run main.py

What MCP clients work with MCP Hub?

MCP Hub works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Conare · memory for coding agents

Turn this server into reusable context

Keep MCP Hub docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Set up free$npx conare@latest