• Access public data insights faster: Data Commons MCP is now hosted on Google Cloud Facebook Twitter LinkedIn Mail In September, 2025, we introduced the Data CommonsModel Context Protocol (MCP) serverto provide a standard way for AI agents to interact with Data Commons data natively. • This was followed by theGemini CLI extension, which streamlined the setup process for Gemini CLI users. • While these tools successfully opened the door for natural language data exploration, they relied on local Python environments, which created some challenges. • Installing and running open-source tools was not compatible with high-security environments; and hosting a local MCP server lacked the scalability needed for developers who want to publish their own query agents. • Today, we’re taking the next step to make it easier for everyone to usedatacommons.orgwith an LLM by launching the hosted Data Commons MCP service in Google Cloud Platform. • Now you can just connect to the free service and let Google manage the rest - no need to worry about Python environments, resource management, version releases, security compliance etc.

Article Summaries:

  • Data Commons has launched a cloud‑hosted version of its Model Context Protocol (MCP) on Google Cloud Platform, replacing the earlier local‑Python implementation. The new service lets users connect to a free, managed MCP endpoint (https://api.datacommons.org/mcp ) without installing or maintaining a local server, addressing security and scalability concerns. Gemini CLI users will automatically switch to the web‑based server, while others can obtain a free Data Commons API key and point their agents to the hosted endpoint. The move aims to simplify natural‑language data exploration and enable developers to build AI agents that query trusted public data sources directly.
  • Data Commons has launched a hosted version of its Model Context Protocol (MCP) on Google Cloud Platform, replacing the earlier local‑Python implementation. The new service allows AI agents and LLMs to query datacommons.org data directly over the web, eliminating the need for users to install and maintain a local MCP server. Developers can now connect with a free API key, while Gemini CLI users will automatically switch to the cloud service in future runs. The hosted MCP supports natural‑language data exploration and can answer statistical queries such as correlations between unemployment and obesity or GDP rankings. Custom Data Commons instances still require a self‑hosted MCP server.

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