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  • F
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    maintenance
    Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.
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    Enables small local models to persist and retrieve long-term user facts through remember and recall tools, using SQLite FTS5 keyword search for lightweight memory without external vector databases or heavy VRAM.
    Apache 2.0
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    quality
    D
    maintenance
    A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.
    327
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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.
    3
    29
    Apache 2.0
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    This read-only MCP Server allows you to connect to Act-On data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp
    MIT
  • A
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    quality
    C
    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
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    quality
    A
    maintenance
    MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.
    MIT
  • A
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    Not graded
    quality
    B
    maintenance
    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.
    2
    MIT
  • A
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    quality
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    maintenance
    A multi-function Streamable HTTP MCP tool aggregation server that provides web search via Brave, Exa, and SearXNG with multi-key rotation and cross-provider fallback, and supports extensible tool families (URL fetch, code search, RAG) through a pluggable architecture.
    MIT
  • A
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    A
    maintenance
    Enables clinical question answering via OpenEvidence with citation verification, including tools to ask questions, retrieve results, and follow up, plus an integrated skill to check citations against primary sources.
    8
    MIT
  • F
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    Not graded
    quality
    C
    maintenance
    Enables MCP-compatible clients to retrieve relevant document chunks and fact-check generated answers against context, classifying them as fully supported, partially supported, or unsupported.
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  • F
    license
    Not graded
    quality
    D
    maintenance
    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
    license
    A
    quality
    B
    maintenance
    Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.
    1
    9 npm
    1
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.
    3
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    A collection of tools that enhance MCP-based workflows with caching, retry logic, batch operations, and rate limiting capabilities.
    7
    9 npm
    MIT