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    Fetch URLs and return clean, LLM-ready markdown with metadata and layered prompt injection defense. Configurable timeouts, word limits, JS rendering, and link extraction. All-in-one MCP server + CLI.
    1
    24 PyPI
    2
    MIT
  • A
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    A Model Context Protocol server that intelligently fetches and processes web content, transforming websites and documentation into clean, structured markdown with nested URL crawling capabilities.
    2
    8 npm
    9
    MIT
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    An MCP server that enables Microsoft Copilot Studio to fetch random jokes from multiple sources including Chuck Norris jokes, Dad jokes, and Yo Mama jokes.
    MIT
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    Enables agents to pull compact MySQL row diffs into their context, supporting before/after changes via triggers or watermark-based updates, with tools to fetch and acknowledge changes.
    MIT
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    Enables AI agents to fetch categorized news headlines and full article text from a multi-topic RSS aggregator, with no API keys required.
    9 npm
    ISC
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    Enables MCP host applications to use configured llms.txt files and fetch documentation URLs from permitted domains through auditable tool calls.
    MIT
  • A
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    C
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    Enables LLM agents to discover and search a catalog of skills, then fetch skill instructions and supporting references, scripts, and assets on demand.
    MIT
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    C
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    Enables clients to search, fetch, and manage entities, relations, notes, sources, pages, media, and status entries in a libSQL-backed personal archive knowledge graph through MCP tools. It also supports a public-only mode that exposes restricted search and fetch access.
    MIT
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    Enables MCP clients to list and fetch content from Notion pages and Google Drive files, returning normalized documents for downstream RAG ingestion.
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  • A
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    MCP server for the full Pāli Tipiṭaka — ~444,000 segments at parity with SuttaCentral (Sutta + Vinaya + Abhidhamma). Hybrid search, full-sutta fetch with cross-references, segment-aligned translation comparison, and Pāli word lookup. Offered as Dhamma Dāna.
    11
    12
    MIT
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    Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.
    3
    MIT
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    Gives local and cloud LLMs live web grounding as four MCP tools: web_search, fetch, deep_search (a token-capped, cited evidence pack sized to a small context window), and research (an agentic search-and-read loop). Flat monthly pricing, no query content stored.
    4
    43 PyPI
    MIT