{
  "markdown": "# DataCommons MCP Server\n\nA Model Context Protocol (MCP) server for accessing Data Commons API data.\n\n## Features\n\n- Search for indicators and topics\n- Get observations and data\n- Support for various data formats and chart configurations\n- HTTP and stdio transport modes\n\n## Installation\n\n### Using pip\n\n```bash\npip install -r requirements.txt\npip install -e .\n```\n\n### Using Docker\n\n```bash\ndocker build -t datacommons-mcp .\ndocker run -p 8000:8000 datacommons-mcp\n```\n\n## Usage\n\n### CLI Commands\n\nStart the server in HTTP mode:\n\n```bash\npython -m datacommons_mcp.cli serve http --host 0.0.0.0 --port 8000\n```\n\nStart the server in stdio mode:\n\n```bash\npython -m datacommons_mcp.cli serve stdio\n```\n\n### Environment Variables\n\n- `GOOGLE_API_KEY`: Your Google API key for Data Commons access\n\n## Development\n\nInstall development dependencies:\n\n```bash\npip install -e \".[dev]\"\n```\n\nRun tests:\n\n```bash\npytest\n```\n\nFormat code:\n\n```bash\nblack .\nisort .\n```\n\n## License\n\nMIT License\n",
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  "sha": "f91ac0f7ccc471d7fcf1a057cc7d931a6381715765e6fdcd07c689b101717d0d",
  "repo_slug": "turnono/datacommons-mcp-server",
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  "api": "https://agentalog.com/api/listings/mcp_ai_smithery_turnono_datacommons_mcp_serv_045f5fa0/readme"
}