Mcp Server Collector
What is Mcp Server Collector
mcp-server-collector is an MCP Server designed to collect information about other MCP Servers available on the internet.
Use cases
Use cases for mcp-server-collector include aggregating MCP Server information for research, monitoring MCP Server availability, and contributing new MCP Servers to the directory.
How to use
To use mcp-server-collector, set up the required .env file with your OpenAI API credentials and the MCP server submit URL. Then, install the necessary configurations for either development or published servers. You can run the server using the specified commands.
Key features
Key features include tools for extracting MCP Servers from URLs and content, and submitting MCP Servers to the MCP Server Directory. It also supports configuration for both development and published environments.
Where to use
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Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mcp Server Collector
mcp-server-collector is an MCP Server designed to collect information about other MCP Servers available on the internet.
Use cases
Use cases for mcp-server-collector include aggregating MCP Server information for research, monitoring MCP Server availability, and contributing new MCP Servers to the directory.
How to use
To use mcp-server-collector, set up the required .env file with your OpenAI API credentials and the MCP server submit URL. Then, install the necessary configurations for either development or published servers. You can run the server using the specified commands.
Key features
Key features include tools for extracting MCP Servers from URLs and content, and submitting MCP Servers to the MCP Server Directory. It also supports configuration for both development and published environments.
Where to use
undefined
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
mcp-server-collector MCP server
A MCP Server used to collect MCP Servers over the internet.
Components
Resources
No resources yet.
Prompts
No prompts yet.
Tools
The server implements 3 tools:
- extract-mcp-servers-from-url: Extracts MCP Servers from given URL.
- Takes “url” as required string argument
- extract-mcp-servers-from-content: Extracts MCP Servers from given content.
- Takes “content” as required string argument
- submit-mcp-server: Submits a MCP Server to the MCP Server Directory like mcp.so.
- Takes “url” as required string argument and “avatar_url” as optional string argument
Configuration
.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"
Quickstart
Install
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
``` "mcpServers": { "fetch": { "command": "uvx", "args": ["mcp-server-fetch"] }, "mcp-server-collector": { "command": "uv", "args": [ "--directory", "path-to/mcp-server-collector", "run", "mcp-server-collector" ], "env": { "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" } } } ```Published Servers Configuration
``` "mcpServers": { "fetch": { "command": "uvx", "args": ["mcp-server-fetch"] }, "mcp-server-collector": { "command": "uvx", "args": [ "mcp-server-collector" ], "env": { "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" } } } ```Development
Building and Publishing
To prepare the package for distribution:
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publish
Note: You’ll need to set PyPI credentials via environment variables or command flags:
- Token:
--tokenorUV_PUBLISH_TOKEN - Or username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
Debugging
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.
Community
About the author
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
