Data Commons MCP Server

This is a Model Context Protocol (MCP) server for fetching public statistical data from Data Commons instances.

Data Commons is an open knowledge repository that provides a unified view across multiple public data sets and statistics. This server allows any MCP-enabled agent or client to query the Data Commons knowledge graph.

Features

• MCP-Compliant: Implements the Model Context Protocol for seamless agent integration.
• Data Commons Access: Fetches public statistics and data from the base datacommons.org knowledge graph.
• Custom Instance Support: Can be configured to work with Custom Data Commons instances.
• Flexible Serving: Runs over both streamable HTTP and stdio.

Quickstart

Prerequisites

1. You must have a Data Commons API key; create one at apikeys.datacommons.org.
2. Install uv by following the official installation instructions.

Configuration

Set the following required environment variable in your shell:

export DC_API_KEY=<your API key>

Start the server

Run the server from your command line in one of two modes:

Streamable HTTP

This runs the server with Streamable HTTP.

# Runs on default port 8080
uvx datacommons-mcp serve http [--port <PORT>]

The server will be available at http://localhost:<port>/mcp.

stdio

This transport mode is intended for local integrations and is programmatically configured within a client (like Gemini CLI settings) to communicate over stdio.

uvx datacommons-mcp serve stdio

Clients

You can use any MCP-enabled agent or client to connect to your running server. For example, see the Data Commons MCP documentation for guides on connecting:

• Google Gemini CLI
• Google ADK natively
• Google ADK in Colab

Or see your preferred client's documentation for how to configure it, using the commands listed above.

Advanced Configuration

Using MCP Tools with a Custom Data Commons

Follow the Guide for using MCP Tools with Custom Data Commons to set additional environment variables required for custom configuration.