Allows AI agents to interact with Canvas LMS by finding relevant resources, retrieving course information, accessing modules and module items, getting file URLs, with planned features for calendar events, assignments, and various analysis capabilities.
Integrates with Google's Gemini API for AI-powered features, specifically for finding relevant resources in Canvas LMS based on natural language queries.
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:
Or, for Cursor IDE to use canvas-mcp with other models:
Or, for Windsurf:
Manual Installation (ONLY for local instances)
Download the repository and run the following commands:
Manual Configuration
Create a .env
file in the root directory with the following environment variables:
Add the following to your mcp.json
or claude_desktop_config.json
file:
Built by Aryan Keluskar :)
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A set of tools enabling AI agents to interact with Canvas LMS, allowing users to find relevant resources, get course information, and navigate modules through natural language queries.
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