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    Enables MCP-compatible clients to read courses, assignments, announcements, files, and grades from a Canvas LMS instance.
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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
    17 PyPI
    2
    MIT
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    Turns Canvas LMS into a scriptable pipeline and exposes it to AI assistants via MCP for querying courses, grades, assignments, and syncing files using natural language.
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    MIT
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    Enables instructors to run their Canvas LMS courses through an AI assistant, with 47 tools for reading rosters, drafting and publishing assignments, building modules, grading submissions, posting announcements, and pulling the full gradebook. Writes are enabled by default while deletes stay off, and everything runs with the instructor's own API token inside the courses they already teach, requiring no administrator or app registration.
    42
    MIT
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    Local-first MCP server for Canvas LMS. Stdio transport, no third-party broker, token stays in ~/.canvas.env. Exposes courses, assignments, modules, announcements, grades, planner items, upcoming events, todo list, and bulk file dump as MCP tools.
    10
    30 PyPI
    4
    MIT
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    A web-fetch MCP server for LLM agents that fetches pages with an escalation ladder through different engines, raising FetchBlocked instead of returning blocked content.
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    3
    Apache 2.0
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    Model Context Protocol server for fetching web content and processing images. This allows Claude Desktop (or any MCP client) to fetch web content and handle images appropriately.
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    658 npm
    41
    MIT
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    An MCP server that turns Claude into a full image production studio, enabling creation, editing, resizing, and brand-consistent asset generation across multiple platforms.
    6
    MIT
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    Lets AI assistants read a student's Canvas LMS courses, modules, deadlines, announcements and course files through the Canvas REST API, using university single sign-on with MFA instead of an API token, and download lecture slides into per-course folders. All access is read-only and works with any Canvas site, defaulting to Oxford.
    9
    1
    MIT
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    Reduces token consumption by 73-87% by cleaning web and API data before it reaches the LLM context window. Supports fetching URLs, searching the web, optimizing JSON, and more.
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    Enables MCP-capable AI tools such as Claude Code and Codex to operate the locally running XuanShang infinite canvas under one unified ruleset: creating projects and certification groups, uploading and certifying images and reference videos, placing assets on the canvas, building Seedance video nodes, submitting generation, and converting drafts to final videos. Credit-spending actions always require explicit user confirmation, and the plugin never reads or stores API keys.
    13
    MIT
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    This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.
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    1
    288,522 PyPI
    91,671
    MIT
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    MCP server for web page fetching (converting to Markdown/text with automatic fallback between Tavily and Firecrawl) and web search via Tavily.
    2
    MIT
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    MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.
    10
    45 npm
    Apache 2.0
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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