A MCP Server used to collect MCP Servers over the internet.
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The server implements 3 tools:
.env file is required to be set up.
OPENAI_API_KEY="sk-xxx"
OPENAI_BASE_URL="https://api.openai.com/v1"
OPENAI_MODEL="gpt-4o-mini"
MCP_SERVER_SUBMIT_URL="https://mcp.so/api/submit-project"
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
To prepare the package for distribution:
uv sync
uv build
This will create source and wheel distributions in the dist/
directory.
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
--token
or UV_PUBLISH_TOKEN
--username
/UV_PUBLISH_USERNAME
and --password
/UV_PUBLISH_PASSWORD
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm
with this command:
npx @modelcontextprotocol/inspector uv --directory path-to/mcp-server-collector run mcp-server-collector
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
{
"mcpServers": {
"fetch": {
"env": {},
"args": [
"mcp-server-fetch"
],
"command": "uvx"
},
"mcp-server-collector": {
"env": {
"OPENAI_MODEL": "gpt-4o-mini",
"OPENAI_API_KEY": "sk-xxx",
"OPENAI_BASE_URL": "https://api.openai.com/v1",
"MCP_SERVER_SUBMIT_URL": "https://mcp.so/api/submit-project"
},
"args": [
"--directory",
"path-to/mcp-server-collector",
"run",
"mcp-server-collector"
],
"command": "uv"
}
}
}
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