Bridge AI assistants with Canvas Learning Management System. 90+ MCP tools for students, educators, learning designers, and developers. Works with Claude, ChatGPT, Cursor, and more.
Comprehensive tools designed for real educational workflows, from simple queries to complex bulk operations.
Ask questions like "What's due this week?" or "Which students haven't submitted?" and get instant answers from your Canvas data.
Execute custom TypeScript for bulk operations with 99.7% token savings. Grade 90 submissions without loading them into context.
FERPA-compliant with automatic data anonymization. Student data is protected before it reaches AI systems.
Track student performance, assignment completion rates, peer review analytics, and more with AI-powered analysis.
Manage discussions, post announcements, facilitate peer reviews, and grade discussion participation efficiently.
Discover APIs with search_canvas_tools, execute TypeScript locally, and build custom integrations with the code API.
Whether you're a student tracking assignments, an educator managing courses, or a learning designer building them, Canvas MCP has you covered.
Get AI-powered assistance with your coursework and stay organized throughout the semester.
Enhance your teaching with powerful tools for course management and student engagement.
AI-powered course design, quality assurance, and accessibility compliance at scale.
Leverage the code execution API for maximum efficiency with custom operations.
Traditional MCP tool calls load every submission into Claude's context. Our code execution API processes data locally, returning only summaries.
import { bulkGrade } from './canvas/grading'; await bulkGrade({ courseIdentifier: "60366", assignmentId: "123", gradingFunction: (submission) => { // Analysis happens locally! const notebook = submission.attachments ?.find(f => f.filename.endsWith('.ipynb')); if (!notebook) return null; return { points: 100, comment: "Great work!" }; } });
Use the hosted server instantly — no Python, no cloning, no setup. Or install locally for full control.
Add this to your MCP client config (Claude Desktop, Cursor, Windsurf, etc.) — replace with your Canvas credentials:
Get your token: Canvas → Account → Settings → New Access Token. Your credentials are sent as headers with each request and never stored on the server.
Privacy: Ideal for students and evaluation. Educators handling FERPA-protected student data should install locally instead.
Clone the repository and set up a Python virtual environment with all dependencies.
Copy the template and add your Canvas API credentials.
Add the server to your Claude Desktop configuration file.
Test your connection and start interacting with Canvas through Claude.
Your data stays safe with local processing and FERPA-compliant anonymization.
Local mode runs on your machine. Hosted mode passes your credentials as HTTP headers per-request — nothing is stored on the server.
Automatic student data anonymization for educators. Real names converted to anonymous IDs.
Students can only access their own data through Canvas API's "self" endpoints.
Your Canvas usage and AI interactions remain completely private.
Pre-built skills that teach AI agents how to use Canvas MCP effectively. Install via skills.sh or use as Claude Code slash commands.
One command to add Canvas workflows to any supported agent.
Student weekly planner. Due dates, submission status, grades, and peer reviews across all courses — prioritized by urgency.
Educator morning dashboard. Submission rates, struggling students, grade distribution, and upcoming deadlines in one view.
Smart grading decision tree. Routes to single, bulk, or code execution based on submission count, with safety-first dry runs.
Full peer review pipeline. Completion analytics, quality analysis, problematic review flagging, targeted reminders, and reports.
Discussion forum facilitation. Browse, read, reply, monitor participation, and post — for both students and educators.
Pre-semester quality audit. Checks structure, content, publishing state, and completeness — generates a prioritized issue report.
WCAG compliance workflow. Scans content, generates prioritized reports, guides remediation, and verifies fixes.
Scaffold complete course structures from specs, templates, or by cloning. Creates modules, pages, assignments, and discussions in bulk.
Have a repetitive Canvas workflow you'd like automated? Submit an issue describing your use case!
Request a SkillCanvas MCP works with any MCP-compatible client.
Join educators and students using AI to make Canvas more powerful and intuitive.