langgraph-docs

Access LangGraph documentation to build stateful agents and multi-agent workflows. Use fetch_url to read: This returns a structured list of all available documentation with descriptions. Identify 2-4 most relevant URLs from the index. Prioritize: Use fetch_url on the selected URLs, then complete the user's request using the documentation content. If fetch_url fails or returns empty content, retry once. If it fails again, inform the user and suggest checking directly. - Fetches official LangGraph Python docs covering state machines, graph-based agent design, and human-in-the-loop patterns - Prioritizes relevant documentation by query type: implementation guides for how-to questions, concept pages for theory, tutorials for end-to-end examples, and API references for technical details - Automatically selects 2–4 most relevant documentation URLs and retrieves their content to answer questions about agent orchestration and LangGraph APIs - Falls back to direct documentation link if fetch operations fail, ensuring users can access source material independently - Implementation questions — specific how-to guides - Conceptual questions — core concept pages - End-to-end examples — tutorials - API details — reference docs