#Langchain

Curated by Archimedes Market with a verified Trust Report. Expose any LangChain chain, agent, or tool as an MCP server. Schema-aware tool registration, tool-call tracing, retry/timeout policies, structured output validation. Bridges the LangChain ecosystem into Claude / ChatGPT / Cursor without rewrites. → archimedes.market/assets/312e3c99-f858-44e7-ba2c-fcaf408825a8.

Preflight spend control for AI agents. Block runaway agent loops before they start - not after the bill arrives. Per-request cost ceilings, budget checks, and outcome-based metering in 2 MCP tool calls.

One endpoint for every AI agent. Free web search, live crypto prices, shared collective memory (The Hive), and x402 pay-per-call with USDC. No signup needed — 10 free calls/day, drop in your agent in 60 seconds.

AES-256-GCM + Argon2id encrypted local vault for AI agent credentials. Store API keys, tokens, and passwords safely. Reference them as {{PLACEHOLDER}} in any AI workflow — LangChain, CrewAI, AutoGen, n8n, and 40+ frameworks.

Xenarch is a non-custodial x402 MCP server. It lets AI agents — Claude, Cursor, LangChain, CrewAI, or any MCP client — resolve HTTP 402 ("Payment Required") responses automatically by signing USDC micropayments on Base L2 (up to $1 per call). Publishers get paid directly through an immutable on-chain splitter contract: 0% fee today, hard-capped at 0.99% forever. Unlike Cloudflare Pay-Per-Crawl, Xenarch works on any host and is fully non-custodial. HTTP 402 has been reserved in the HTTP spec since 1997 — x402 is the open protocol that finally uses it.

Persistent memory for AI agents that survives across sessions. Store, recall, and semantically search memories. Includes loop detection that catches agents stuck repeating themselves, full audit trails, shared memory between agents, and a real-time dashboard. Works with Claude Code, Claude Desktop, and Cursor. Open source, free tier available.

Official MinerU MCP server for document parsing. Convert PDF, DOCX, PPTX, images, and HTML to high-quality Markdown. Supports 109-language OCR, table/formula extraction, and both token-free Flash mode (20 pages / 10MB) and Precision mode (600 pages / 200MB). Works with Claude Desktop, Cursor, and Windsurf.

Streaming AI agent API built on LangGraph. Implements AG-UI, A2A, MCP, and x402 simultaneously. Agents discover it via A2A, call it over SSE, use its tools via MCP, and pay per request in USDC on Base. Per-org MCP federation, pgvector memory, 16 built-in Web3 tools, and dual billing (Stripe + x402).

EU AI Act compliance scanning for Python AI agents. 10 tools that scan, analyze, and fix compliance gaps across LangChain, CrewAI, AutoGen, OpenAI, and RAG pipelines. Checks 6 EU AI Act articles with HMAC-SHA256 tamper-evident audit trails. pip install air-blackbox-mcp. August 2026 deadline ready.

PinRAG is a retrieval-augmented generation (RAG) MCP server built with LangChain and Chroma. Index PDFs, plain text, Discord exports, YouTube transcripts, and GitHub repositories, then ask questions in Cursor, VS Code (Copilot), or any MCP-capable client. Answers include citations (pages, timestamps, paths). Install via PyPI (`pipx`, `uv tool`, or `uvx --from pinrag pinrag-mcp`). Configure API keys in your editor’s MCP `env` block.

Git for agent memory. Memstate gives AI agents versioned, structured memory with automatic conflict detection, full version history, and up to 80% fewer tokens than vector-based alternatives. Extracts facts from text and markdown into structured keypaths, with 84.4% accuracy on the open-source benchmark vs 20.4% for Mem0.

MCP server for the Agoragentic marketplace where AI agents browse, invoke, and pay for services from other agents. 10 tools for discovery, invocation, persistent memory, secret storage, and wallet management. Payments in USDC on Base L2.

Multi-agent orchestration MCP server with atomic shared blackboard, FSM governance, per-agent budget enforcement, and adapters for 12 AI frameworks including LangChain, AutoGen, CrewAI, and OpenAI Assistants.

A production-ready MCP server that exposes LangChain agent capabilities through the Model Context Protocol. Provides multi-step reasoning with ReAct pattern, tool support (web search, weather lookup), and is deployed on Google Cloud Run for scalable, serverless operation.

GitHub AI Agent powered by official GitHub MCP Server. Uses LangGraph and LangChain MCP Adapters. Agent is exposed on various agent transport protocols (AGNTCY Slim, Google A2A, MCP Server)

langchain-based client for proxmox mcp server - co-pilot experiment

This repository contains all source code for AIOS (Langchain server, Website, Desktop application). This will be a good example using MCPs

E14Z - AI Tool Discovery Platform. The npm for AI agents to discover and connect to MCP servers.

🚀 mcp-use is a TypeScript library that makes it easy to connect LangChain.js-compatible LLMs with MCP servers. Build powerful, flexible AI agents with dynamic tool access and multi-server support.

Python library for integrating the Alation API into agentic workflows

The llm_to_mcp_integration_engine is a communication layer designed to enhance the reliability of interactions between LLMs and tools (like MCP servers or functions).

This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, CrewAI, RAG, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.

A Model Context Protocol server that facilitates interaction with the Solana blockchain, built using the Ping Agent Kit. (

Servidor MCP para ciberseguridad en Windows. Expone herramientas defensivas como APIs HTTP listas para ser usadas por agentes IA, Claude Desktop o scripts personalizados. Fácil de integrar, extensible y listo para automatizar tu defensa digital.

It is a modular and extensible AI agentic server system that connects specialized agents through a central REST API. These agents can analyze code repositories, fetch external data (like weather), generate text summaries, and remember past interactions using a persistent memory manager.

Agent-to-Agent (A2A) communication protocol for inter-agent coordination and a Model Context Protocol (MCP)-inspired architecture for interacting with external tool servers.

Quarkus Langchain4J Workshop

A practical demonstration of integrating LangChain with Model Control Protocol (MCP) featuring both single and multi-server implementations. Includes examples of mathematical computations and weather queries using async operations, React agents, and OpenAI integration. Perfect for developers looking to understand MCP-LangChain integration patterns.

Alris is an AI automation tool that transforms natural language commands into task execution.

Simple Multi-Server MCP Client with LangChain

This repo is dedicated to learning and working with large language models (LLMs), prompt engineering, and modern GenAI tools such as LangChain, RAG, and vector databases.

Tool-based LLM integration with Zenodo via the Model Context Protocol (MCP)

Repo for demonstrating simple Model Context Protocol (MCP) server with several Agent Frameworks

The Search For A Refined Coding ChatGPT for Software Engineers

🚀 mcp-use is a TypeScript library that makes it easy to connect LangChain.js-compatible LLMs with MCP servers. Build powerful, flexible AI agents with dynamic tool access and multi-server support.

This repo is for Praticing the Langgraph,Langchain,AI Automation and other stuff along with these MCP server,client implementation

Desktop application for managing Model Context Protocol servers (MCP). Provides a centralized interface to configure and manage MCP servers for use with LLMs and AI assistants such as Claude.

This Streamlit application provides a user interface for connecting to MCP (Model Context Protocol) servers and interacting with them using different LLM providers (OpenAI, Anthropic, Google...).

MCP (Minimal Command Protocol) server that allows users to search for documentation from popular libraries such as LangChain, LlamaIndex, and OpenAI using the Serper API. The server fetches search results and extracts the relevant documentation from the web using HTTP requests and BeautifulSoup.

This sample implements the Langchain MCP adapter to the Box MCP server.

Transforms MCP tools into collaborative, reasoning agents using modern agent frameworks.

AgentChat 是一个与Agent交流的平台，包含默认Agent，并支持自定义Agent，可以实现多轮问答使Agent帮助用户想实现的功能。该项目技术栈包括LLM、LangChain、Function call、ReAct、MCP、Milvus、ElasticSearch、RAG、FastAPI

This project demonstrates a decoupled real-time agent architecture that connects LangGraph agents to remote tools served by custom MCP (Modular Command Protocol) servers. The architecture enables a flexible and scalable multi-agent system where each tool can be hosted independently (via SSE or STDIO), offering modularity and cloud-deployable execut

LangGraph agent tutorial adapted to use MCP servers.

A Repository of Functions Consumable by Other Agent Frameworks

A Go adapter that bridges LangChain Go tools with Model Context Protocol (MCP) servers.

Demo of implementation of MCP using Langchain MCP Adapters and Ollama

Addapter that turns MCP server tools into langchain usable tools

💬 MaxKB is an open-source AI assistant for enterprise. It seamlessly integrates RAG pipelines, supports robust workflows, and provides MCP tool-use capabilities.

LangChain Agent with MCP Servers: Using LangChain MCP Adapters for tool integration.

Quick Start MCP with Langchain

Developed an MCP-based AI infrastructure enabling real-time tool execution, structured knowledge retrieval, and dynamic agentic interactions for AI clients like Claude and Cursor.

Simple MCP Server w/ Shell Exec. Connect to Local via Ngrok, or Host Ubuntu24 Container via Docker

Learning how to build mcp-servers to connect in llms via langchain

A MCP (model context protocol) server that gives the LLM access to and knowledge about databases

Simple MCP Server w/ Shell Exec. Connect to Local via Ngrok, or Host Ubuntu24 Container via Docker

** THIS REPO HAS MOVED TO

Example of using MCP servers, both over sdio + sse. Also using langchain-mcp

Unlock 650+ MCP servers tools in your favorite agentic framework.

Adapters for integrating Model Context Protocol (MCP) tools with LangChain.js applications, supporting both stdio and SSE transports.

Simple CLI MCP Client Implementation Using LangChain ReAct Agent / Python

MCP Tools Usage From LangChain ReAct Agent / Example in TypeScript

Simple CLI MCP Client Implementation Using LangChain ReAct Agent / TypeScript

A simple CLI to run LLM prompt and implement MCP client.

🦜🔗 LangChain Model Context Protocol (MCP) Client

Package intended to simplify the use of MCP server tools within LangChain

Unlock 650+ MCP servers tools in your favorite agentic framework.