Create, build, and publish Python MCP servers to PyPI — conversationally.
MCP Creator is a meta-tool that helps anyone create their own MCP servers. Install it, add it to your AI assistant, and the assistant walks you through the entire process: naming your package, checking PyPI availability, scaffolding a complete project with FastMCP, building, publishing, and pushing to GitHub. It remembers your setup across sessions so returning creators skip straight to building. Zero configuration required — just describe what you want to build and it handles the rest. Perfect for beginners who want to create and share their own MCP tools.
Valid MCP server (2 strong, 8 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
10 files analyzed · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Add this to your MCP configuration file:
{
"mcpServers": {
"mcp-creator": {
"args": [
"mcp-creator"
],
"command": "uvx"
}
}
}Once installed, try these example prompts and explore these capabilities:
From the project's GitHub README.
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.
pip install mcp-creator
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": []
}
}
}
| 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 |
Once your server is on PyPI, list it on MCP Marketplace to reach thousands of AI users:
Run generate_launchguide after publishing to create your submission file, then submit at mcp-marketplace.io/submit.
check_pypi_name to verify availability on PyPIscaffold_server with your tool definitions — generates a complete, runnable projectservices/ with your real API callsbuild_package → publish_package → live on PyPIsetup_github creates a repo and pushes your codegenerate_launchguide creates the submission file with your repo URLFor 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.
git clone https://github.com/gmoneyn/mcp-creator.git
cd mcp-creator
uv venv .venv && source .venv/bin/activate
uv pip install -e ".[dev]"
pytest -v
Add the mcp-creator python plugin
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