Provides comprehensive access to Canvas LMS functionality including course management, assignments, grades, messaging, calendar events, to-do lists, modules, announcements, file access, quizzes, and user search capabilities.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Canvas MCP Serverwhat assignments are due this week?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Canvas MCP Server
A Model Context Protocol server providing comprehensive access to Canvas LMS for AI assistants.
Features
Access Canvas LMS functionality through 31 MCP tools:
Courses: List and view course information
Assignments: Browse, view details, check submissions, and submit work
Grades: View grades for individual courses or across all courses
Messaging: Send and receive messages, manage conversations (read/unread, star, archive, delete)
Calendar: View events and upcoming deadlines
To-Do Lists: Track pending tasks and assignments
Modules: Navigate course content structure
Announcements: Read course and institutional announcements
Files: Access and download course materials
Quizzes: View quizzes and submissions
Users: Search for classmates and instructors
Installation
Prerequisites
Bun runtime
Canvas LMS account with API access token
Setup
Install dependencies:
bun installGet your Canvas API token:
Log into Canvas
Navigate to Account → Settings
Scroll to "Approved Integrations"
Click "+ New Access Token"
Generate and copy the token
Configure environment variables:
export CANVAS_BASE_URL="https://your-institution.instructure.com"
export CANVAS_ACCESS_TOKEN="your_access_token_here"Configure your MCP client with the following settings:
{
"mcpServers": {
"canvas": {
"command": "bun",
"args": ["run", "/absolute/path/to/canvas/src/index.ts"],
"env": {
"CANVAS_BASE_URL": "https://your-institution.instructure.com",
"CANVAS_ACCESS_TOKEN": "your_access_token_here"
}
}
}
}Usage
After setup, interact with Canvas through your MCP client:
Show me all my current courses
What assignments do I have due soon?
What are my grades in all my classes?
Show me my recent Canvas messagesDevelopment
Quality Gates
bun run format # Format code with Prettier
bun run lint # Lint code with ESLint
bun run typecheck # Type check with TypeScript
bun test # Run testsBuild
bun run build # Build for production
bun run dev # Run in development modeDocumentation
Architecture
Built with TypeScript and the MCP SDK, this server provides a type-safe interface to the Canvas LMS REST API. All operations use Bearer token authentication and respect Canvas rate limits.
Project Structure
canvas/
├── src/
│ ├── canvas/
│ │ ├── client.ts # Canvas API client
│ │ └── client.test.ts # Client tests
│ └── index.ts # MCP server implementation
├── docs/ # Documentation
├── package.json # Dependencies and scripts
└── tsconfig.json # TypeScript configurationSecurity
Store credentials in environment variables
Never commit access tokens to version control
Use token expiration dates
Rotate tokens regularly
Follow your institution's API usage policies
API Reference
This server implements the Canvas LMS REST API v1. For detailed API documentation, visit the Instructure Developer Portal.
License
This project uses permissive open-source dependencies with no telemetry or tracking.