langgraph-docs

To fetch LangGraph documentation, the agent reads the docs index at langchain.com/llms.txt, identifies 2-4 relevant URLs, and applies those pages to answer questions about graph agents and agent orchestration.

The best way to find LangGraph how-tos and API references is fetching the documentation index, which prioritizes selecting 2-4 relevant URLs focused on implementation guides, core concepts, end-to-end tutorials, and API details.

Yes, you can lookup specific LangGraph docs without loading the entire index by fetching the docs index first, then selecting and fetching only 2-4 most relevant pages to generate focused, citation-backed responses.

If the LangGraph docs fetch returns empty content, the fetch_url workflow retries once. If it still fails, you should direct users to the LangGraph documentation site at langchain-ai.github.io/langgraph/.

Yes, the LangGraph docs fetcher covers agent orchestration concepts by selecting pages from the docs index that prioritize core concepts, implementation how-tos, end-to-end tutorials, and API references for graph agents.