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    Canvas Mcp

    Collection of Canvas LMS and Gradescope tools for the model context protocol. Query your courses, find resources, and chat with your upcoming assignments.

    8 stars
    TypeScript
    Updated Oct 4, 2025
    anthropic
    canvas
    mcp
    python
    uv

    Table of Contents

    • Features
    • Usage
    • Installing via Smithery (Preferred)
    • Manual Configuration (ONLY for local instances)

    Table of Contents

    • Features
    • Usage
    • Installing via Smithery (Preferred)
    • Manual Configuration (ONLY for local instances)

    Documentation

    Canvas MCP

    Canvas MCP is a set of tools that allows your AI agents to interact with Canvas LMS and Gradescope.

    gradescope

    example

    Features

    • Find relevant resources - Ability to find relevant resources for a given query in natural language!
    • Query upcoming assignments - Not only fetch upcoming assignments, but also provide its breakdown for a given course.
    • Get courses and assignments from Gradescope - Query your Gradescope courses and assignments with natural language, get submission status, and more!
    • Get courses
    • Get modules
    • Get module items
    • Get file url
    • Get calendar events
    • Get assignments
    • and so much more...

    Usage

    Note down the following beforehand:

    1. Canvas API Key from Canvas > Account > Settings > Approved Integrations > New Access Token

    2. Gradescope Email and Password https://www.gradescope.com/

    Installing via Smithery (Preferred)

    To install Canvas MCP for Claude Code via Smithery:

    bash
    npx -y @smithery/cli@latest mcp add aryankeluskar/canvas-mcp --client claude-code

    Or, for Cursor IDE to use canvas-mcp with other models:

    bash
    npx -y @smithery/cli install aryankeluskar/canvas-mcp --client cursor

    Or, for ChatGPT:

    1) Enable Developer Mode in settings, if not already enabled

    2) Go to ChatGPT Settings > Connectors and click Create to add this server URL: https://canvas-mcp--aryankeluskar.run.tools

    ---

    Manual Configuration (ONLY for local instances)

    Create a .env file in the root directory with the following environment variables:

    code
    SNITHERY_API_KEY=your_snithery_api_key

    Add the following to your mcp.json or claude_desktop_config.json file:

    json
    {
      "mcpServers": {
          "canvas": {
              "command": "npx",
              "args": [
                  "-y",
                  "@smithery/cli",
                  "run",
                  "@aryankeluskar/canvas-mcp"
              ]
          }
      }
    }

    ---

    Built by Aryan Keluskar :)

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