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Canvas MCP

Collection of Canvas LMS and Gradescope tools for the ultimate EdTech model context protocol. Allows you to query your courses, find resources, and chat with upcoming assignments in the AI app of your choice. try now!

Canvas MCP

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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. Gemini API key from https://aistudio.google.com/app/apikey
  3. Gradescope Email and Password https://www.gradescope.com/

Installing via Smithery (Preferred)

To install Canvas MCP for Claude Desktop automatically via Smithery:

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

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

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

Or, for Windsurf:

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

Manual Installation (ONLY for local instances)

Download the repository and run the following commands:

git clone https://github.com/aryankeluskar/canvas-mcp.git
cd canvas-mcp

# Install dependencies with uv (recommended)
pip install uv
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -r requirements.txt

# Or install with pip
pip install -r requirements.txt

Manual Configuration

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

CANVAS_API_KEY=your_canvas_api_key
GEMINI_API_KEY=your_gemini_api_key

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

{
  "mcpServers": {
      "canvas": {
          "command": "uv",
          "args": [
              "--directory",
              "/Users/aryank/Developer/canvas-mcp",
              "run",
              "canvas.py"
          ]
      }
  }
}

Built by Aryan Keluskar :)

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