"With the introduction of the Developer Knowledge API and the accompanying Model Context Protocol server, the company aims to address a structural problem that many AI assistants encounter today: working with outdated or incomplete technical documentation. The range of AI-driven developer tools is growing rapidly, from agentic platforms to command-line interfaces. At the same time, it is becoming increasingly important for these tools to have reliable and up-to-date knowledge."
"With the Developer Knowledge API, Google explicitly positions its official documentation as a programmatic source of truth. Instead of relying on outdated training data or vulnerable forms of web scraping, developer tools can directly request documentation in Markdown format. This covers a wide range of sources, including Firebase, Android, and Google Cloud. During the public preview, new or updated documentation is reindexed within a day, so AI systems quickly have access to the latest information."
"Parallel to the API, Google is introducing a Model Context Protocol server. This protocol acts as a standardized and secure way for AI assistants to consult external data sources. By linking the MCP server to an IDE or assistant, such a system effectively gains read access to the official documentation. This makes it possible to provide more reliable answers to questions about implementation choices, troubleshooting, and comparing cloud services in specific scenarios."
Google introduced the Developer Knowledge API and a Model Context Protocol (MCP) server to make official developer documentation accessible to AI tools. The API allows developer tools to request documentation in Markdown from sources including Firebase, Android, and Google Cloud, and reindexes new or updated docs within a day during public preview. The MCP server provides a standardized and secure method for AI assistants to consult external data sources and gain read access from IDEs or assistants. Together these technologies aim to reduce reliance on outdated training data or web scraping and enable more reliable, up-to-date answers about implementation, troubleshooting, and service comparisons.
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