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Showing 1–24 of 2,139 for LangChain.js MCP Adapters

MCP Docs Search Server

This is a lightweight, plug-and-play MCP server that empowers any LLM to dynamically search and retrieve up-to-date documentation from popular AI libraries…

Fast LLM & Agents & MCPs

This repo covers LLM, Agents, MCP Tools, Skills concepts with sample codes: LangChain & LangGraph, AWS Strands Agents, Google Agent Development Kit…

Velocirag

# 🦖 VelociRAG **Lightning-fast RAG for AI agents.** _Four-layer retrieval fusion powered by ONNX Runtime. No PyTorch. Sub-200ms warm search. Incremental graph…

🌐 MCP-Server-101

This project 🌐 is a robust implementation of the Model Context Protocol (MCP), designed to facilitate seamless integration and interaction with various…

Mcp Client Typescript

The MCP Docs Server is a Node.js implementation of a Model Context Protocol (MCP) server that provides a powerful tool to search and retrieve up-to-date…

Solon Ai

Java AI application development framework (supports LLM-tool,skill; RAG; MCP; Agent-ReAct,Team-Agent). Compatible with java8 ~ java25. It can also be embedded…

Skill Seekers

Transform 17 source types (docs, GitHub repos, PDFs, videos, Jupyter, Confluence, Notion, Slack/Discord) into AI-ready skills and RAG knowledge. 35 MCP tools…

PinRAG

PinRAG is a retrieval-augmented generation (RAG) MCP server built with LangChain and Chroma. Index PDFs, plain text, Discord exports, YouTube transcripts, and…

Documentation Search

Provides a documentation search tool that retrieves the latest Python library documentation from LangChain, LlamaIndex, and OpenAI through targeted Google…

Library Docs MCP Server

Search and fetch documentation for popular libraries like Langchain, Llama-Index, and OpenAI using the Serper API, providing updated information for LLMs.

Munin Ai Memory

Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on…

MCP Knowledge Base

A knowledge base and experimental playground for exploring the Model Context Protocol (MCP)—understanding how hosts, servers, LLMs, and tools interact.