Google pairs Docs MCP and Developer Skills to keep Gemini coding agents current

On Apr 01, 2026, Google published a practical guide for improving Gemini-based coding agents by combining Gemini API Docs MCP with Gemini API Developer Skills. The company starts from a blunt diagnosis: coding agents can generate outdated Gemini API code because their training data has a cutoff date, so even strong models may miss current SDK patterns, newer model names, or recently changed documentation.

Docs MCP is Google's answer to the freshness problem. It connects a coding agent to current Gemini API documentation, SDK references, and model information through the Model Context Protocol. That means the agent is not forced to rely only on what was present during pretraining; it can look up live product information at generation time and align its answers with the current docs surface.

Developer Skills addresses a different failure mode. Instead of only supplying raw documentation, it adds best-practice instructions, resource links, and patterns that push the agent toward Google's recommended SDK usage. In other words, one tool improves access to current facts, while the other improves the default behavior the agent applies when assembling code and setup instructions.

Google says the combined setup reached a 96.3% pass rate on its eval set.

The same setup used 63% fewer tokens per correct answer than vanilla prompting.

The official onboarding path is published at ai.google.dev/gemini-api/docs/coding-agents.

The broader significance is that API providers are starting to ship control planes for third-party coding agents, not just model endpoints. If this approach works, documentation freshness and prescribed agent skills become part of the product itself, which could reduce one of the most persistent causes of agentic coding errors: confidently generating code for an API surface that has already moved on.