"A workflow for processing and summarizing voice recordings into meeting notes and sending emails" matching MCP servers:

A self-hosted MCP server for storing, searching, and querying meeting notes with semantic search and RAG capabilities using SQLite + OpenRouter.

Automatically synchronizes meeting transcripts from Otter.ai to a local SQLite database for easy browsing and management. It enables semantic and keyword-based search across meeting history through integrated MCP tools for Claude and Cursor.

A personal knowledge management system that transforms daily notes into organized, searchable knowledge using the Model Context Protocol.

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.

MCP server for processing raw book notes into structured, searchable knowledge using embeddings and semantic search.

Provides SQL-backed semantic search over indexed notes using pgvector, exposing tools to search and list note sources via natural language.

Enables AI assistants to search and edit Apple Notes on macOS using semantic search, with safe write operations and full local indexing.

Enables querying, listing, and summarizing personal knowledge base documents using RAG with hybrid search and LLM.

A Model Context Protocol server that enables semantic search and RAG over your Apple Notes, allowing AI assistants like Claude to search and reference your notes during conversations.

MCP server that indexes your Obsidian notes into a Milvus vector database and enables querying them via a local or OpenAI LLM, with real-time synchronization.

Enables semantic search and RAG (Retrieval Augmented Generation) over your Apple Notes.

Turns markdown note directories into an MCP knowledge assistant server, enabling hybrid search, explanations, quizzes, and comparisons for any MCP-compatible AI tool.

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.

Enables AI assistants like Claude to search and reference your Apple Notes using semantic search and RAG capabilities, with fully local execution and no API keys required.

Enables managing and searching markdown notes with semantic search, question answering, and note generation, and provides an MCP server for GitHub Copilot integration.

A local MCP server that enables full-text and semantic search over your own Telegram chats using your personal MTProto login, with everything running locally.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.