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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.
    Last updated
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    Apache 2.0
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    Enables AI assistants to perform defensive security tasks such as vulnerability detection, CVE lookup, phishing/link safety checks, and security report generation via MCP tools.
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    Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.
    Last updated
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    MIT
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    A FastMCP-based server providing a comprehensive toolset for the RunningHub AI application platform. It enables users to configure nodes, upload media, submit AI tasks, and manage task execution and results through persistent storage.
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    Provides tools to search, download, and manage satellite imagery from all Copernicus Sentinel missions via the Copernicus Data Space ecosystem. It enables advanced geospatial queries, temporal coverage analysis, and automated data management for Earth observation tasks.
    Last updated
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    LGPL 3.0
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    A template and demonstration project for building, testing, and deploying remote MCP servers using FastMCP and uv. It provides a foundational structure for creating MCP-compliant tools that can be hosted publicly and integrated with LLM agents.
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    MCP server for business-day arithmetic with country-aware holiday calendars. It offers tools to check, calculate, and list business days and holidays for over 60 countries.
    Last updated
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    MIT
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    Enables AI assistants to search and filter Azure platform updates, including previews, general availability, and retirements, through natural language queries.
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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 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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    Provides policy-based access control, incident tracking, and compliance monitoring to govern AI agent behavior. It enables organizations to enforce security rules and maintain audit trails by validating agent actions against trust levels and pattern-based policies.
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    Enables AI assistants to query KumoRFM for predictive analytics on relational data, including graph management, natural language to PQL conversion, and training-free predictions.
    Last updated
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    MIT
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    Use 3,000+ pre-built cloud tools from Apify, known as Actors, to extract data from websites, e-commerce, social media, search engines, maps, and more
    Last updated
    10
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    MIT
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    Exposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.
    Last updated
    9
    MIT