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    Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.
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    34 PyPI
    MIT
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    Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.
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    MIT
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    Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.
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    Enables AI assistants to write and debug integration tests by providing live access to DOM structure and executing code directly in test environments.
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    51 npm
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    MIT
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    Enables agents to perform local metasearch, scholarly and code/model lookups, and fetch rendered web pages or PDFs as paginated markdown, including stealth browsing and arXiv paper overviews.
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    MIT
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    Connect AI assistants to your Gramps Web family tree. Search and edit genealogy records, explore ancestors, descendants, relationships and timelines, and read document scans with vision-capable models. Includes guided research workflows, source citations, read-only mode, and privacy-aware media previews. Install with Docker or a Claude Desktop bundle.
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    AGPL 3.0
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    MCP server for AI-powered web research — search (Google, Brave, Serper, SearXNG), scrape any page, extract PDFs/DOCX/YouTube transcripts, academic & patent search. Single Go binary. Works with Claude, Cursor, Copilot, and any MCP client.
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    MIT
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    Enables AI-assisted user feedback collection and management via a web interface, with MCP integration for automated replies and tool execution.
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    17 npm
    MIT
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    An MCP server that enables AI assistants to perform web searches on Perplexity.ai using browser automation instead of an official API. It supports persistent authenticated sessions and returns search results along with cited sources directly to the client.
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    42 npm
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    MIT
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    Search and resolve MCP server packages on the mpak registry, enabling agents to discover servers, inspect tools, and check credential requirements before installation.
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    MIT
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    Enables natural-language interaction with Ladybug Tools for building performance simulation, 3D modeling, and data visualization, allowing agents to perform complex environmental analysis tasks without CAD software.
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    35 PyPI
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    GPL 3.0
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    MCP server for querying Google Gemini Web from Claude Code and other MCP clients, using cookie-based authentication. Enables creating, continuing, listing, viewing, and deleting Gemini chat conversations with model and thinking mode control.
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    AGPL 3.0
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    Provides an LLM client with self-hosted web scraping capabilities including scraping, crawling, mapping, searching, structured data extraction, browser interaction, and deep research, without reliance on paid proxy or CAPTCHA services.
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    GPL 3.0
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    Provides a web search tool with citations by running Claude Code CLI in an isolated Docker container, enabling search even in environments without direct Anthropic web search support.
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    An MCP server for global tech intelligence gathering, offering tools for searching Chinese and English web content, GitHub trending, arXiv papers, HN, Exa, SEC filings, Juejin, Zhihu, Bilibili, and A-share financial reports, all without API keys and with direct China access.
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    MIT
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    Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.
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    Apache 2.0
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    Bridges the editing capabilities of an already-open DingTalk document in the browser to any MCP host via standard stdio, forwarding tools to the page's internal MCP server over a local WebSocket. Supports read/write operations through suggested edits, pairing-based security, and zero runtime dependencies.
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    9 npm
    MIT
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    Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.
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    180 PyPI
    3
    MIT