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

Enables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.

Enables deterministic auditing of RAG retrieval faithfulness and hallucination scores, providing structured JSON output for AI agents and MCP-compliant clients.

The MCP server provides tools for entity extraction, query refinement, and relevance checking to enhance RAG applications by integrating with OpenAI and Gemini.

This MCP server enables interactive chat with AI models via the Anthropic API, supporting document retrieval and command-based prompts.

An evaluation harness that probes MCP-based retrieval servers for calibration, relevance, coverage, citation integrity, and more, also exposing the probes as MCP tools for assistants and CI agents.

An open-source MCP server providing AI agents with neural web search via Exa and tiered web fetch (Exa, local browser, Firecrawl) as a drop-in replacement for built-in web tools, preserving provenance and guarding against SSRF.

An AI conversation management layer that enables creating chat sessions, persisting message history to GitHub, and performing semantic searches over past interactions. It supports multi-turn threading and context injection to integrate external memory sources into Claude conversations.

Enables reading channels and messages, finding users, and sending messages and files to bbw-chat.de (Synology Chat) from any MCP client.

Enables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).

Enables image and video generation using BigModel AI's CogView and CogVideoX models via MCP, supporting batch image generation and various configuration options.

Enables interactive command-line chat with AI models via the Anthropic API, supporting document retrieval with @mentions and slash-command prompts with tab auto-completion.

Enables interactive chat with AI models and document retrieval via the Anthropic API, supporting command-based prompts and MCP tool integrations.

A Model Context Protocol server that analyzes webpage design structures, providing detailed layout, navigation, content, form, image, and link information from a given URL.

A modular RAG service framework that exposes tools like query_knowledge_hub, list_collections, and get_document_summary via MCP protocol, enabling AI assistants to perform retrieval-augmented generation.

Enables document ingestion, semantic search, and retrieval-augmented generation via MCP tools and REST API, using vector embeddings and intelligent chunking.

Enables MCP-capable agents to generate and edit images through Gemini or OpenAI, returning an absolute file path instead of image bytes to keep context windows clean.

MCP server for publishing AI agent conversations as public links with optional password protection and expiration, also providing tools to revoke shared chats and retrieve link metadata.

MCP server for Google Chat that enables managing spaces, messages, members, reactions, attachments, and GIFs through the Model Context Protocol.

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

Enables AI agents to chat and exchange notes through simple HTTP GET requests, with support for signed identities, private rooms, and long-polling, all exposed as MCP tools.