"LangGraph" matching MCP servers:

A clean, modular Model Context Protocol server implementation for LangGraph documentation, designed for easy extensibility with tools and resources.

MCP server implementing clean architecture with LangGraph for building and managing agent workflows.

Provides a standardized interface to interact with LangGraph agents through ChatGPT Enterprise, enabling conversational AI workflows with tools for agent invocation, streaming responses, and thread management.

A terminal-based MCP server that provides tools like web search, URL fetching, note management, and calculations, and connects them to a LangGraph ReAct agent for multi-step tasks.

Provides six tools including web search, URL fetching, calculator, and note management for use with LangGraph agents or manual testing via terminal.

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

A production-ready agent system that automatically discovers and uses tools from MCP servers using LangGraph's ReAct architecture and LLM-powered routing.

Enables LLM-powered agents to securely communicate with and orchestrate downstream microservices via FastAPI endpoints exposed as MCP tools.

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.

Turns a shopping list FastAPI app into an MCP server, enabling a LangGraph chatbot to manage shopping lists via natural language.

MCP server for AWS DynamoDB CRM data, enabling LangGraph agents to discover and call tools to retrieve customer accounts and support tickets via the Model Context Protocol.

A LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents.

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.

Enables AI-powered research by breaking a topic into subtopics, gathering information via agents, and compiling a report. Integrates with LangGraph and RAG for orchestration and contextual retrieval.

A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.

An MCP server that exposes vehicle-diagnostic and CAN-bus domain logic as agent tools, with a LangGraph orchestration layer and a human-in-the-loop eval harness.

Provides an MCP interface to the ERA RINF railway infrastructure database for Poland and Czech Republic, enabling route planning, train compatibility checks (gauge, axle load, length, clearance), weather risk assessment, and traction planning, with a LangGraph agent integrating a custom MCP server and an OpenWeather MCP server.

MCP server that lets coding agents test AI agents. Create YAML test cases, snapshot golden baselines, check for regressions, and generate visual reports all from inside Claude Code or any MCP-compatible tool. Works with LangGraph, CrewAI, OpenAI, Claude, Mistral, and any HTTP API.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

MCP server for AI-native L1 support: triages tickets, answers from a knowledge base, escalates to L2 via Telegram/GitHub, and manages feedback, with a LangGraph workflow and safety guardrails.