Skip to content

aksbdc/agent-toolkit

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Data Commons MCP Server

This is an experimental MCP server for fetching public information from Data Commons.

This is experimental and subject to change.

Requirements

  1. A Data Commons API key. You can get one from apikeys.datacommons.org.
  2. uv. You can find installation instructions at https://astral.sh/uv.

Getting Started

Run the server with uvx:

stdio

DC_API_KEY=<your-key> uvx datacommons-mcp serve stdio

http

This will run the server with SSE on port 8080. You can access it at http://localhost:8080/sse.

DC_API_KEY=<your-key> uvx datacommons-mcp serve http

Debugging

You can start the MCP inspector on port 6277. Look at the output for the pre-filled proxy auth token URL.

DC_API_KEY=<your-key> npx @modelcontextprotocol/inspector uvx datacommons-mcp serve stdio

IMPORTANT: Open the inspector via the pre-filled session token url which is printed to terminal on server startup.

  • It should look like http://localhost:6274/?MCP_PROXY_AUTH_TOKEN={session_token}

Then to connect to this MCP server, enter the following values in the inspector UI:

  • Transport Type: STDIO
  • Command: uvx
  • Arguments: datacommons-mcp serve stdio

Click Connect

Testing with Gemini CLI

You can use this MCP server with the Gemini CLI.

Edit your ~/.gemini/settings.json file and add the following, replacing <your api key> with your actual API key:

{
  ...
  "mcpServers": {
    "datacommons-mcp": {
      "command": "uvx",
      "args": [
        "datacommons-mcp",
        "serve",
        "stdio"
      ],
      "env": {
        "DC_API_KEY": "<your api key>"
      }
    }
  }
}

About

Tools and agents for interacting with the Data Commons Knowledge Graph using the Model Context Protocol (MCP).

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages

  • Python 100.0%