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    Enables AI agents to access and manage project guidelines, documentation, and context through a structured content system with template support and workflow management.
    37
    47 PyPI
    MIT
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    Provides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.
    MIT
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    A minimal MCP server that enables searching through pre-scraped React documentation using a hybrid approach combining DuckDB full-text search and transformer-based reranking.
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    Enables an assistant to watch a cooking video once and then guide a hands-free cook through it: importing videos into validated step-by-step guides, navigating steps, searching timestamped transcript and on-screen evidence, showing exact frames and clip replays, and setting persistent timers across restarts. Sessions, progress, and deadlines are stored so users can resume where they left off.
    5
    MIT
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    Provides deterministic parental guidance for children with chronic kidney disease, including food safety checks, lab report interpretation, and nutrient-aware food substitutions based on authoritative guidelines and the Chinese Food Composition Table.
    12
    MIT
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    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
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    Enables agents to turn a plain-language description of a device into a complete, validated build package — parts list, 3D-printable parts, wiring, firmware code, picture assembly guide, and tests — that anyone can assemble without electronics experience.
    1
    MIT
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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.
    1
    20 PyPI
    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.
    3
    39 PyPI
    29
    Apache 2.0
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    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
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    Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.
    14
    Apache 2.0
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    One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose
    4
    3
    MIT
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    Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.
    12
    5 npm
    1
    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.
    4
    MIT