"LangGraph" matching MCP servers:

Enables MCP-compatible hosts to retrieve LangGraph documentation through retrieval-augmented generation, with source attribution for responses.

Provides MCP-compatible hosts with retrieval-augmented access to LangGraph documentation, enabling Claude and other assistants to answer questions with relevant, source-attributed context.

Enables retrieval-augmented question answering over LangGraph documentation, allowing MCP-compatible hosts to query a semantic vector store and receive context-aware responses with source attribution.

Retrieval-Augmented Generation system serving LangGraph documentation through the Model Context Protocol, enabling semantic search and context-aware responses.

Exposes a RAG agent built with LangGraph, enabling retrieval-augmented question answering over a PostgreSQL/pgvector corpus via the MCP protocol.

An MCP server that utilizes LangGraph and Google Gemini to conduct comprehensive research through multi-iteration deep searches and quick results. It provides high-quality analysis with automated citations and grounding metadata for thorough investigations.

Enables running durable, traceable AI agents via LangGraph through a universal MCP interface, integrating with Hatchet for orchestration, logging, and retries. Provides tools for knowledge management (ingestion, RAG) and Kubernetes operations (diagnosis, auto-fix).

MCP server that mimics a food delivery assistant, enabling natural language ordering, personalized recommendations, order tracking, and review/policy queries via a LangGraph ReAct agent with human-in-the-loop approval.

Exposes document ingestion, retrieval (vector, vectorless, hybrid), and multi-turn chat tools for a LangGraph-powered RAG pipeline with streaming answers.

Enables Claude to search and retrieve documents from Azure AI Search indexes with intelligent summarization and analysis using LangGraph workflows and optional Google Gemini integration.

A LangGraph-powered research agent that performs iterative web searches using Google Search and Gemini models to generate structured reports with citations. It integrates with MCP-compatible clients like Claude and Cursor to enable sophisticated, multi-step AI research workflows.

Enables semantic search over OpenAPI endpoint catalogs using FAISS and LangGraph, returning grounded technical recommendations for natural-language API queries.

Provides semantic search across the entire LangChain ecosystem, including documentation and source code for LangChain, LangGraph, LangSmith, and DeepAgents.

An MCP-compatible RAG backend using LangGraph and FastAPI, enabling chaining of AI model logic with document context search.

An autonomous AI software engineer and MCP server that uses LangGraph and a hybrid RAG index to autonomously edit, test, and debug codebases.

Enables retrieval-augmented generation search and chat over documents stored in Azure Blob Storage, with a Streamlit app for uploading files and interacting via a LangGraph agent.

Exposes GoHighLevel (GHL) sub-account tools to Anthropic-powered LangGraph agents, enabling Claude models to interact with GHL contacts, pipelines, and automations via the Model Connection Protocol.

Enables hybrid search over policies using Reciprocal Rank Fusion and provides grounded, context-aware answers via a LangGraph agent with COSTAR prompting.

A conversational AI server that enables users to search Wikipedia and retrieve information through natural language interactions using LangGraph and Model Context Protocol (MCP).

Provides file system access for resume matching through JSON-RPC, enabling semantic search and workflow orchestration with LangGraph.