"RAG (Retrieval-Augmented Generation) MCP Integration for ChatGPT" matching MCP servers:

Private tooling to stage ChatGPT conversations into reviewable Homebase markdown and Notion drafts with redaction and classification.

Enables querying Google NotebookLM notebooks directly from Claude Desktop (MCP) and Claude Code (CLI), providing citation-backed answers from Gemini.

A local proxy that enables ChatGPT to access an Obsidian vault through the Obsidian Local REST API by tunneling via ngrok and adding the API key header.

A local-first Graph-RAG system combining ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q&A over Obsidian vaults, supporting MCP clients like Claude Desktop, Cursor, and Raycast.

This MCP server bridges ChatGPT web with an Obsidian vault, allowing ChatGPT to read and write notes via the Obsidian Local REST API.

MCP server that integrates with LM Studio to provide a search_notes tool, allowing the chat model to retrieve and answer from a local Obsidian vault.

Enables semantic and keyword search over Obsidian-style Markdown knowledge bases by registering any folder as a vault, with support for incremental indexing, raw source reads, and cache-backed embeddings over MCP stdio.

MCP server for hybrid retrieval over markdown vaults, combining sqlite-vec embeddings and FTS5 keywords with reciprocal rank fusion, plus optional cross-encoder reranking.

Enables semantic search over an Obsidian vault using natural language, retrieving relevant notes and extracted conclusions.

Enables semantic search and reading of Obsidian Markdown notes through read-only MCP tools, allowing Claude to retrieve relevant passages from a local vault.

Answers questions about a folder of markdown notes using hybrid retrieval that fuses FTS5 keyword search and vector search, then reranks results with a cross-encoder.

Persists Claude Code sessions to Notion as team memory, enabling queryable recall of decisions, work state, and project architecture.

Enables semantic search and retrieval over an Obsidian vault using local or API-based embeddings, allowing AI assistants to find notes by meaning, get related content, and pull context during conversations.

Provides semantic search over Obsidian markdown notes using BAAI/bge-m3 embeddings and ChromaDB, accessible via the Model Context Protocol.

MCP server for Obsidian vaults, optimised for Cursor agents — safe note editing, lean tool surface, direct filesystem access.

Enables semantic search and content retrieval from local Obsidian vaults through the Model Context Protocol. It allows AI assistants to query notes by meaning, filter by tags, and access full note content for enhanced knowledge integration.

A live MCP server that connects AI assistants to a running Obsidian instance, enabling full app automation including reading notes, clicking UI elements, managing plugins, and executing JavaScript.

A Python MCP server for note management with RAG capabilities, enabling adding, searching, asking questions, summarizing, and deleting notes, using PostgreSQL and ChromaDB with Google Gemini for embeddings and generation.

A robust MCP server that transforms OneNote notebooks into an AI-accessible knowledge base for Gemini Spark, enabling natural language queries to list, read, and search notes via Microsoft Graph API.

Enables Claude to manage a personal todo list in Notion, with capabilities to add, view, and complete tasks.