"Updated documentation for LangChain, Langraph, Node.js, Express, and FastAI frameworks" matching MCP servers:

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

A utility that integrates Model Context Protocol (MCP) into Express applications, offering both stateful session management and stateless request handling options.

An MCP server exposing document search, retrieval, and summarization tools, paired with a LangChain agent that performs multi-step tasks like finding and summarizing relevant docs.

Enables full-text search and paginated retrieval of indexed documentation (PDFs, Markdown, text) through MCP tools, with filtering by category and file.

Exposes LangChain and Anthropic Claude capabilities as tools for generating production-ready RAG systems, Supabase vector stores, and document ingestion pipelines. It enables users to instantly scaffold AI infrastructure and document processing code through natural language prompts in MCP-compatible clients.

Exposes LangChain agent capabilities through the Model Context Protocol, enabling multi-step reasoning tasks with ReAct pattern execution via a production-ready FastAPI service deployed on Google Cloud Run.

An MCP server integrating LangChain, RAG, and Agent to provide knowledge retrieval and tool invocation through natural language.

Enables grounding AI responses in a local document corpus by exposing MCP tools to list, search, and summarize documents, and generating answers using OpenAI.

Local-first document management and semantic search for AI coding agents, with a built-in web dashboard and REST API.

Enables MCP clients such as Cline, Cursor, and Claude Desktop to query official LangChain documentation using hybrid retrieval, returning source-linked snippets and full documents to ground answers and reduce hallucination.

An MCP server that enables users to fetch and audit documentation from user-defined llms.txt index files. It provides tools to list documentation sources and retrieve content from specific URLs with built-in domain access controls for secure context retrieval.

Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.

Provides MCP tools for searching, retrieving, and answering questions about indexed Nextcloud developer documentation from multiple sources.

Enables AI agents to search and query documentation from git repositories using hybrid search and structured metadata queries.

A stateless Model Context Protocol server that implements a simple echo functionality with resource, tool, and prompt components, enabling LLMs to echo back messages through standardized MCP interactions.

A basic Model Context Protocol server implementation that demonstrates core functionality including tools and resources for AI chat applications.

A Multi-Server Control Plane system that enables natural language querying of job listings and employee feedback data through two specialized servers built with LangChain.

Enables AI agents to manage, upload, chunk, and semantically search local documents through MCP tools and a REST API, with a built-in web dashboard and optional Gemini-powered AI search.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

A basic example of a serverless Model Context Protocol (MCP) server implemented using Netlify Functions with Express, enabling AI agents to interact with custom capabilities.