canvas-mcp
Canvas MCP is a toolset designed to enhance AI interactions with Canvas LMS and Gradescope, featuring capabilities like resource finding and assignment querying using natural language. It simplifies managing educational content across platforms.
Canvas MCP
Canvas MCP is a set of tools that allows your AI agents to interact with Canvas LMS and Gradescope.
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:
- Canvas API Key from
Canvas > Account > Settings > Approved Integrations > New Access Token
- Gemini API key from https://aistudio.google.com/app/apikey
- 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 :)