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    Provides a read-only PostgreSQL SQL surface for LLM agents via MCP, with defense-in-depth security layers for safe database queries.
    Last updated
    3
    MIT
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
    Last updated
    3
    27
    Apache 2.0
  • F
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    A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.
    Last updated
    15
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    Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.
    Last updated
    1
    MIT
  • F
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    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.
    Last updated
    4
  • A
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    Jinni is a tool to efficiently provide Large Language Models the context of your projects. It gives a consolidated view of relevant project files complete with metadata, overcoming the limitations and inefficiencies of reading files one by one. The philosophy behind this tool is that LLM context wi
    Last updated
    2
    270
    Apache 2.0
  • A
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    A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.
    Last updated
    MIT
  • F
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    Exposes any SQLite database as read-only MCP tools for AI assistants, enabling listing tables, describing schemas, and running SELECT queries with filtering, ordering, and pagination.
    Last updated
  • A
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    Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.
    Last updated
    MIT
  • A
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    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.
    Last updated
    2
    MIT