"Chat with RAG (Retrieval-Augmented Generation)" matching MCP servers:

Provides a local chat room for coordinating work across Git worktrees, coding agents (Claude, Codex), and humans, with tools to start, wake, stop, message, and search agent sessions.

Enables remote control of the Cursor AI agent via chat platforms like GitHub Issues or Telegram, allowing users to start sessions and receive summaries and prompts in a chat thread.

Enables remote chat between Feishu (Lark) and AI agents like Cursor/Claude via MCP, allowing users to send messages from Feishu groups and receive streaming replies.

Wraps Tool and ToolPackage instances from the llm-chat ecosystem behind the Model Context Protocol, enabling stdio and Streamable HTTP transports for MCP servers.

Exposes local stdio MCP servers to chat AIs through temporary public URLs, providing both a Streamable HTTP gateway and a REST+OpenAPI bridge for integration with ChatGPT and other clients.

Enables AI coding agents to collaborate on the same project by sharing session briefs and reading each other's native transcripts, memories, and instructions in place, with zero-copy, across different agent tools.

Enables AI agents to send messages to human users via chat platforms (currently Discord) and optionally wait for human responses, facilitating human-in-the-loop interactions.

Enables agents to inspect configured LLM models and send chat requests to them, with support for parameter overrides, file-based prompts, and output to files.

Enables AI assistants to perform retrieval-augmented generation with hybrid search, reranking, multi-modal image processing, and RAG evaluation through standardized MCP tools.

MCP server providing tools for entity extraction, query refinement, and relevance checking to build Agentic RAG applications.

An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.

Implements a RAG workflow that integrates with any custom knowledge base and can be triggered directly from the Cursor IDE.

Connects a RAG application to open-webui using Model Context Protocol (MCP), enabling server-to-client communication for context retrieval and tool usage in remote environments through Server-Sent Events (SSE).

基于MCP协议的聊天桥接服务器，允许多个AI Agent接入同一个聊天室进行对话协作。

Provides MCP (Model Control Protocol) tools for accessing and interacting with Google Chat spaces and messages through OAuth2 authentication.

Enables real-time communication and shared vector memory between Claude Code, OpenAI Codex CLI, and Google Gemini CLI. It allows different AI platforms to exchange messages, share context, and collaborate through a unified MCP interface.

Enables AI agents to access user and message data through MCP resources, providing REST API integration for user management with paginated lists and thread tracking.

Enables ChatGPT to load explicitly selected engineering skills via a minimal MCP interface, keeping the skill catalog out of tool schemas and serving validated runtime bundles locally.

An MCP server that lets multiple agent sessions (e.g., Claude Code, Claude Desktop) on the same machine communicate over shared channels like walkie-talkies, enabling them to exchange messages and coordinate tasks without any central broker.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.