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75,634 servers. Updated
20 Best Email MCP Servers — compared and ranked, August 2026Ranked from 1,989 matching servers on stars, growth, downloads and maintenance. Updated .

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"A tool for converting emails into 5-minute podcasts" matching MCP servers:

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    A Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.
    Apache 2.0
  • A
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    C
    maintenance
    An integration server implementing the Model Context Protocol that enables LLM applications to interact with Milvus vector database functionality, allowing vector search, collection management, and data operations through natural language.
    240
    Apache 2.0
  • F
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    B
    maintenance
    Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: * Multi-Project Support: Isolate memories into separate "brains" (Context Cores). * GraphRAG: Automatically builds a knowledge graph from your context. * Sub-200ms Search: Blazing fast Hybrid & Semantic
    3
  • F
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    A local Retrieval-Augmented Generation system that enables users to ingest markdown files into a FAISS-powered vector knowledge base for semantic search. It provides tools for document indexing and context retrieval to support informed LLM queries without external dependencies.
  • F
    license
    A
    quality
    D
    maintenance
    An MCP server for semantic search and retrieval of indexed Slack messages stored in Qdrant using Cohere reranking via AWS Bedrock. It enables users to search through Slack history, retrieve full message threads, and access channel or user statistics through natural language.
    5
  • A
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    D
    maintenance
    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.
    MIT
  • A
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    A server implementation that allows secure communication between MCP clients and privateGPT, enabling users to chat with privateGPT using knowledge bases and manage sources, groups, and users through a standardized Model Context Protocol.
    6
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    A local-first personal RAG memory system that turns AI conversation history into a searchable, retrievable knowledge base via MCP, enabling LLMs to semantically search past conversations.
    2
    8
    AGPL 3.0
  • A
    license
    A
    quality
    B
    maintenance
    A personal memory MCP server that ingests AI agent conversation logs from multiple platforms into a searchable PostgreSQL+pgvector database, enabling cross-session recall of past reasoning and decisions.
    6
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Myelin provides persistent, brain-inspired memory for AI agents, enabling cross-session and cross-tool context retention with local, private storage.
    11
    9
    MIT
  • F
    license
    A
    quality
    A
    maintenance
    Local-first agent-memory MCP server with a why() tool: recall a fact together with its connected subgraph (multi-hop), so linked memories surface even when they share no words with the query. remember/recall/relate/forget/why over one fused vector + graph + columnar engine a single offline Rust binary.
    8
    87
  • A
    license
    A
    quality
    B
    maintenance
    An MCP server that incrementally indexes repositories and documents into a Postgres + pgvector store using CocoIndex, and exposes semantic search over them.
    3
    1
    MIT
  • A
    license
    B
    quality
    B
    maintenance
    Local-first knowledge retrieval MCP server that turns private text documents into a source-backed knowledge base, enabling retrieval, comparison, summaries, and review outlines for any local MCP client while keeping source paths and index operations visible.
    12
    1
    MIT
  • A
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    quality
    A
    maintenance
    MCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.
    MIT