Which integrations are available for this server?

Automates the process of initializing git repositories, creating new repositories on GitHub, and pushing the scaffolded MCP server code. Enables checking for package name availability and publishing built Python MCP server packages to the Python Package Index (PyPI).

How do I use mcp-creator?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@mcp-creator Help me build an MCP server that searches Spotify playlists." That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

mcp-creator

Create, build, and publish Python MCP servers to PyPI — conversationally.

Install mcp-creator, add it to your AI assistant, and it walks you through the entire process: naming your package, scaffolding a complete project, building, and publishing to PyPI.

Install

pip install mcp-creator

Setup

Add to Claude Code (~/.claude/settings.json):

{ "mcpServers": { "mcp-creator": { "command": "mcp-creator", "args": [] } } }

Or for Cursor (.cursor/mcp.json):

{ "mcpServers": { "mcp-creator": { "command": "mcp-creator", "args": [] } } }

Tools

Tool	What it does
`get_creator_profile`	Load your persistent profile — setup status, project history. Called first every session.
`update_creator_profile`	Save setup state, usernames, and project history across sessions
`check_setup`	Detect what's installed (uv, git, gh, PyPI token) — only walks through missing steps
`check_pypi_name`	Check if a package name is available on PyPI
`scaffold_server`	Create a complete MCP server project from a name + description + tool definitions
`add_tool`	Add a new tool to an existing scaffolded project
`build_package`	Run `uv build` on the project
`publish_package`	Run `uv publish` to PyPI
`setup_github`	Initialize git, create a GitHub repo, and push the code
`generate_launchguide`	Create LAUNCHGUIDE.md for marketplace submission

How It Works

Tell your AI what you want to build: "I want an MCP server that checks the weather"
It checks the name: calls check_pypi_name to verify availability on PyPI
It scaffolds the project: calls scaffold_server with your tool definitions — generates a complete, runnable project
You fill in the logic: replace the TODO stubs in services/ with your real API calls
Build & publish: build_package → publish_package → live on PyPI
Push to GitHub: setup_github creates a repo and pushes your code
Submit to marketplace: generate_launchguide creates the submission file with your repo URL

What Gets Generated

For a project named my-weather-mcp with a get_weather tool:

my-weather-mcp/ ├── pyproject.toml ← hatchling build, mcp[cli] dep, CLI entry point ├── README.md ← install instructions + MCP config JSON ├── .gitignore ├── src/my_weather_mcp/ │ ├── __init__.py │ ├── server.py ← FastMCP + @mcp.tool() for each tool │ ├── transport.py │ ├── tools/ │ │ ├── __init__.py │ │ └── get_weather.py │ └── services/ │ ├── __init__.py │ └── get_weather_service.py ← TODO: your logic here └── tests/ ├── test_server.py └── test_get_weather.py

The generated server runs immediately — stub services return placeholder data so you can test before implementing real logic.