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76,502 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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"Tools to Automate Sales Outreach Emails" matching MCP servers:

  • A
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    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
  • A
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    quality
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    maintenance
    Enables semantic search across Apple Mail, Messages, Calendar, and Contacts on macOS using natural language queries. All processing happens locally with privacy-first vector indexing for fast similarity search.
  • F
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    C
    maintenance
    MCP server that ingests PDF documents into pgvector for semantic search and RAG pipelines. It handles extraction, chunking, local embeddings, and storage, enabling agents to make PDFs searchable via natural language.
  • A
    license
    D
    quality
    C
    maintenance
    A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.
    1
    2
    MIT
  • A
    license
    B
    quality
    D
    maintenance
    Enables Claude to interact with core AWS services like S3, EC2, RDS, and CloudWatch, along with a generic SDK wrapper for any AWS operation. It also supports cost monitoring and optional vector store capabilities for document ingestion and search.
    10
    3
    The Unlicense
  • A
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    quality
    B
    maintenance
    Enables natural language search and analysis of uploaded PDF, CSV, and Excel documents using retrieval-augmented generation and MCP tools, providing contextual answers to user queries.
    MIT
  • F
    license
    B
    quality
    D
    maintenance
    A service discovery and proxy for MCP servers that enables registration, discovery, and execution of tools on remote MCP servers. Uses vector-based similarity search through Alibaba Cloud services to intelligently route requests to appropriate MCP services.
    3
  • A
    license
    C
    quality
    D
    maintenance
    Enables AI agents to interact with INFINI Easysearch (compatible with Elasticsearch/OpenSearch APIs) through 121 tools covering cluster management, index operations, document manipulation, search queries, snapshots, and monitoring.
    100
    4
    MIT
  • A
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    quality
    C
    maintenance
    An interface for managing and querying MariaDB databases that supports standard SQL operations alongside advanced vector and embedding-based search capabilities. It enables AI assistants to seamlessly integrate relational and vector data workflows through a standardized protocol.
    189
    MIT
  • A
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    quality
    D
    maintenance
    A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.
    12
    MIT
  • A
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    quality
    C
    maintenance
    RAGX MCP Server enables retrieval-augmented generation with document ingestion, hybrid search, and agentic answering using Claude, exposing tools for querying, searching, and managing documents.
    2
    MIT
  • A
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    quality
    C
    maintenance
    Wraps n8n with an MCP server and vector storage to enable semantic search, management, and execution of automated workflows. It integrates with other tools to make workflows searchable and orchestratable within a larger automation ecosystem.
    1
    MIT
  • A
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    Not graded
    quality
    D
    maintenance
    An MCP server for RAG using Qdrant that automatically indexes documents from directories and generates search tools for each collection.
    MIT
  • A
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    quality
    C
    maintenance
    A minimal MCP server with four tools (add, greet, text_stats, divide) demonstrating typed parameters, structured outputs, and error handling over stdio transport.
    MIT
  • A
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    Not graded
    quality
    D
    maintenance
    Enables AI assistants to interact with MariaDB databases through standard SQL operations and advanced vector/embedding-based search. Supports database management, schema inspection, and semantic document storage and retrieval with multiple embedding providers.
    MIT
  • A
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    quality
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    maintenance
    Exposes LangChain and Anthropic Claude capabilities as tools for generating production-ready RAG systems, Supabase vector stores, and document ingestion pipelines. It enables users to instantly scaffold AI infrastructure and document processing code through natural language prompts in MCP-compatible clients.
  • A
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    quality
    D
    maintenance
    Local-first AI memory layer with hybrid retrieval and brain-inspired namespaces. Enables agents to save, search, and manage memories directly via MCP tools.
    5
    MIT