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    MCP server for querying your local Google Takeout activity (Search/YouTube history) via SQLite/FTS5. Provides tools for keyword search, activity stats, and database info, enabling AI assistants to cite your personal history.
    3
    MIT
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    Enables structural framing analysis of documents, identifying perspectives, omissions, and reader positioning, with numerical claim verification against authoritative sources.
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    Apache 2.0
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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.
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    Apache 2.0
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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.
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    MIT
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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.
    17
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    A Model Control Protocol server that integrates with Claude Desktop to enable simultaneous querying and cross-checking of responses from multiple LLM providers including OpenAI, Anthropic, Perplexity AI, and Google Gemini.
    15
    MIT
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    Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.
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    MCP server enabling natural-language querying of SQLite databases via schema discovery, GraphRAG retrieval, and safely guarded read-only SQL execution.
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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.
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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.
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    MIT