Up-to-date documentation you can talk to, for every repo in the world (deepwiki.com)

A new Go implementation of the Model Context Protocol (MCP) was announced, aiming to let LLM applications seamlessly access external data sources and tools. By standardizing how models request and receive structured context and invoke external capabilities, MCP in Go makes it straightforward to build “talkable” living documentation for code repositories—turning README, code, and CI/issue data into an up‑to‑date conversational interface. The release plugs into the broader open-source stack (RAG engines like RAGFlow, model runtimes such as Llama 3.3, Phi‑4, Gemma 3, Mistral, and tool platforms like Dify/Langflow), enabling low‑latency, production‑grade integrations in Go services. For AI/ML engineers this is significant because it lowers the friction of connecting retrieval-augmented generation, tool invocation, and observability into real apps. Technically, MCP provides a protocol for exchanging context blobs, tool descriptions, and structured responses so agents can retrieve documents, call test/playback tools (e.g., Playwright), generate diagrams, or surface live repo metadata securely and consistently. Combined with open model stacks and RAG pipelines, the Go MCP can accelerate building deployable assistants, repo-aware code search/docs, and multi-model agent orchestration while preserving performance and deployment control.