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  • AWS MCP Server

    Havoc24k
    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.
    Last updated
    10
    3
    The Unlicense

  • slack-indexed

    KanvaBhatia-Alaan
    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.
    Last updated
    5

  • AVS Document Search System

    patw
    A
    license
    -
    quality
    D
    maintenance
    A vector search system that enables semantic retrieval of document chunks using MongoDB Atlas Vector Search and Voyage AI embeddings, allowing users to search documents by meaning rather than just keywords.
    Last updated
    2
    MIT

  • docs-mcp

    globalion
    A
    license
    -
    quality
    C
    maintenance
    Upload documents (Word, Excel, PDF, PowerPoint) to a vector RAG store and perform semantic search with page-level citations. Queries are free; ingestion costs credits at break-even pricing.
    Last updated
    MIT

  • Solr MCP

    allenday
    A
    license
    -
    quality
    D
    maintenance
    A Python server that enables AI assistants to perform hybrid search queries against Apache Solr indexes through the Model Context Protocol, combining keyword precision with vector-based semantic understanding.
    Last updated
    20
    MIT

  • Headless Codebase Indexer

    y1hanh
    F
    license
    -
    quality
    D
    maintenance
    A minimalist indexing tool that provides AI agents with semantic search and structural AST parsing for deep codebase understanding. It enables autonomous agents to navigate large codebases predictably using vector embeddings and native language server capabilities like definition and reference tracking.
    Last updated