langchain-docs-search

name	langchain-docs-search
description	Search Langchain and LangGraph documentation using the langchain-docs MCP. Load when the user asks about Langchain/LangGraph APIs, concepts, or version-specific behavior you are not certain about.

Langchain / LangGraph docs search

Use the langchain-docs MCP tools to look up accurate, version-specific information before answering questions about:

• langchain, langchain-core, langchain-community APIs
• langgraph graph construction, nodes, edges, state, checkpointers
• langchain-openai, langchain-anthropic, langchain-ollama integrations
• langchain-mcp-adapters and other ecosystem packages

Never hallucinate API signatures, parameter names, or class hierarchies. If uncertain, search first.

When to search

Signal	Action
User asks "how do I use X in LangGraph"	Search before answering
User pastes a deprecation warning or error	Search the affected symbol
You're unsure about a parameter name/default	Search the class or function
User asks about a feature added after 2024	Always search — training data may be stale

Query patterns

Good queries are specific: library + symbol + what you need.

# Good
"LangGraph StateGraph add_node signature"
"langchain-core RunnableConfig configurable fields"
"LangGraph AsyncSqliteSaver from_conn_string"
"langchain-ollama ChatOllama streaming"

# Too vague
"langchain"
"how does langchain work"

Typical flow

1. Call the docs search tool with a specific query.
2. Read the returned excerpts — prefer the official API reference over guides when you need exact signatures.
3. Cite the relevant doc section in your reply so the user can follow up.
4. If the first result is insufficient, refine the query (add version, narrow the symbol name).

Do not use for

• General Python questions unrelated to the Langchain ecosystem.
• Questions the user has already answered with their own code snippet.
• Chinook / SQL questions — use sql-agent for those.