canvas-mcp
Provides tools for accessing Canvas LMS courses, assignments, grades, discussions, announcements, and messaging, with dry-run safety on write operations.
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@followed by the MCP server name and your instructions, e.g., "@canvas-mcpwhat assignments are due this week?"
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Here is a step-by-step guide with screenshots.
canvas-mcp
A Model Context Protocol server that gives AI agents structured access to Canvas LMS — coursework, deadlines, grades, submissions, discussions, and messages — over the official REST API.
Works with any Instructure-hosted Canvas instance. Built and validated against canvas.okstate.edu.
Contents
Why the REST API
Canvas exposes a stable, versioned API at /api/v1/. Wrapping it — rather than scraping the web UI — yields:
Single-call actions instead of multi-page navigation.
Resilience to UI redesigns; the API is versioned.
Compact, structured JSON that doesn't flood an agent's context with rendered HTML.
Simple auth via one bearer token.
Browser automation is reserved for things genuinely outside Canvas — embedded LTI tools such as zyBooks, Cengage, or Coursera quizzes, whose contents Canvas itself cannot see.
Features
11 workflow-oriented tools spanning the full student workflow, designed for agent ergonomics (human-readable names over opaque IDs, consolidated multi-step actions).
Dry-run safety on every write — nothing is submitted, posted, or sent without an explicit
confirm: true.Cross-course planner — one call returns everything due across all courses.
Zero-config secrets — the server auto-loads a local
.env, so no token ever appears on a command line or in client config.Tested — offline boot check in CI plus a live contract/regression suite.
Tools
Tool | Description | Access |
| Active courses with code, term, and current grade | read |
| Everything due soon across all courses (via the planner) | read |
| Assignments in a course with due dates and submission status | read |
| Full detail: instructions, rubric, accepted types, your status | read |
| Course grade summary, or per-assignment feedback and rubric | read |
| Recent announcements, all courses or one | read |
| List discussion topics, or read a full thread | read |
| Resolve a name to a user ID for messaging | read |
| Submit a text entry, URL, or uploaded file | write |
| Reply to a discussion topic | write |
| Send a Canvas inbox message | write |
Installation
Requirements: Node.js ≥ 22.
git clone https://github.com/tylergibbs1/canvas-mcp.git
cd canvas-mcp
npm install
npm run buildConfiguration
Generate a token in Canvas: Account → Settings → "+ New Access Token". Treat it like a password.
cp .env.example .env # then set CANVAS_TOKENVariable | Required | Description |
| yes | Your Canvas origin, e.g. |
| yes | A personal access token. |
The server reads .env automatically. Real environment variables take precedence, so you may also pass these inline if you prefer.
Usage
Claude Code
The server auto-loads .env, so no secret is needed on the command line:
claude mcp add --scope user canvas -- node /absolute/path/to/canvas-mcp/dist/index.jsClaude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"canvas": {
"command": "node",
"args": ["/absolute/path/to/canvas-mcp/dist/index.js"],
"env": {
"CANVAS_BASE_URL": "https://your-school.instructure.com",
"CANVAS_TOKEN": "your_token_here"
}
}
}
}Any MCP-compatible client works — point it at node dist/index.js with the two environment variables set.
Write safety
Every write tool defaults to a dry run: it validates inputs and returns a preview of exactly what would be sent, but performs no action. You must re-call with confirm: true to actually submit, post, or send. An accidental or hallucinated call cannot change anything in Canvas.
Development
npm run dev # run from source with tsx
npm run build # compile TypeScript to dist/
npm test # offline: boot the server and verify all tools register (no token)
npm run eval # live: contract/regression suite (requires a token)
npm run inspect # interactive MCP Inspector (requires a token)Evaluation
eval/eval.mjs(npm run eval) asserts data-independent invariants against the live API — deadline ordering, valid status values, HTML stripping, cross-tool grade consistency, and that every write tool'sconfirm:falsepath returns a dry run and never executes.eval/tasks.mdprovides realistic agent task prompts (happy path, multi-step, write safety, scope boundary) for behavioral evaluation, each with "what good looks like."
Security
Tokens are secrets.
.envis git-ignored; never commit it. Anyone with your token can act as you in Canvas.Scoped to your account. The server can only do what your Canvas account can do.
Revocation. Remove a token anytime in Canvas under Account → Settings → Approved Integrations.
Tokens are sent only to your configured
CANVAS_BASE_URLover HTTPS.
Contributing
Issues and pull requests are welcome. Please run npm run build and npm test before opening a PR; if you have a Canvas token available, npm run eval is encouraged.
License
MIT © Tyler Gibbs
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