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    MCP server that parses web pages into clean markdown via Crawl4AI's HTTP API, exposing parse_page and health-check tools with configurable proxy and timeout.
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    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.
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    Apache 2.0
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    Provides LLMs with real-time web search and content extraction capabilities, including text/news search, full-text URL reading, and targeted technical documentation search.
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    MIT
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    Enables AI agents and users to query Perplexity AI's premium models (GPT-5.4, Claude 4.6 Opus, Gemini 3.1 Pro, etc.) via MCP tools, CLI, or API, with support for deep research, model council, and multi-turn conversations.
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    MIT
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    MCP server providing 22 tools to query Perplexity AI's premium models (GPT-5.4, Claude 4.7 Opus, etc.) with citations, source discovery, and rate limit checking for AI agents.
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    MIT
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    Enables human-in-the-loop interaction for AI coding workflows through native desktop dialogs that present route choices, text input, and image annotation capabilities when AI assistants encounter decision points.
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    MIT
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    A Model Context Protocol server built with FastMCP that provides tools for retrieving the current local date and time. It allows LLMs to access precise temporal information directly from the host environment.
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    MIT
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    Unofficial MCP server wrapping crawl4ai that enables extraction and analysis of content from web pages, PDFs, Office documents, YouTube videos, and more, with AI-powered summarization and Google search integration to reduce token usage while preserving key information.
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    MIT
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    Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.
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    MIT
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    Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.
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    Apache 2.0
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    Enables AI assistants to query, analyze, and discover FileMaker database schemas via OData v4, with pandas-powered analytics for efficient data summaries.
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    GPL 3.0
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    MCP server for querying the SEC Ownership Graph, providing curated read-only tools to analyze activist campaigns, control chains, and board interlocks from SEC filings. Answers cite accession numbers and abstain when data is insufficient.
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    MIT
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    Enables AI assistants to render 3D models from OpenSCAD code, generating single views or multiple perspectives with full camera control. Supports animations, custom parameters, and returns base64-encoded PNG images for seamless integration.
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    MIT
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    Enables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.
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    Enables management of Kylas CRM lead operations, including creating leads, searching and filtering records, and resolving user, product, or pipeline IDs. It provides specialized tools for monitoring idle leads and accessing lead schema instructions through natural language.
    8
    MIT
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    Bridges a local AI agent to a Colab session in the browser, enabling code execution and file operations through the Model Context Protocol.
    9
    Apache 2.0