Canvas LMS MCP Server

The TypeScript MCP server for Canvas LMS.

MCP server for Canvas LMS. Read courses, assignments, submissions, rubrics, quizzes; grade, comment, manage course content, and handle Canvas admin workflows from any AI agent.

119 tools across Canvas courses, assignments, submissions, gradebook history, rubrics, quizzes, New Quizzes (LTI), files, users, groups, enrollments, discussions, modules, pages, calendar, conversations, peer reviews, accounts, analytics, outcomes, student workflows, dashboard, instructor attention workflows, and health checks. Three deployment modes: stdio, HTTP, and library import.

One-click install (Claude Desktop)

1. Download canvas-lms-mcp.mcpb from the latest release.
2. Double-click the file (or drag it into Claude Desktop's Extensions settings).
3. When prompted, paste your Canvas API token and Canvas API base URL (e.g. https://school.instructure.com/api/v1). Teachers and staff handling student data can also flip FERPA mode — pseudonymize students on in the same dialog (what it does).

No terminal, no Node.js install, no config-file editing — Claude Desktop bundles the runtime and handles config for you. The same .mcpb works in Claude Code and MCP for Windows.

Prefer the terminal? Use the Quick Start below.

Comparison

	canvas-lms-mcp	vishalsachdev/canvas-mcp	DMontgomery40/mcp-canvas-lms
Language	TypeScript	Python	TypeScript
Tools	119	80+	54
License
Last commit

Quick Start

1. Get a Canvas API Token

1. Log in to your Canvas instance
2. Go to Account > Settings
3. Scroll to Approved Integrations and click + New Access Token
4. Give it a name (e.g., "MCP Server") and click Generate Token
5. Copy the token immediately -- you won't see it again

2. Run the Setup Wizard

npx canvas-lms-mcp init

The wizard detects your installed AI clients (Claude Desktop, Cursor, VS Code, Windsurf, Codex, Continue, Claude Code), prompts for your Canvas token and base URL, validates the credentials against your Canvas instance, and writes the config for every client you select.

add-mcp is also supported as a generic alternative: npx add-mcp canvas-lms-mcp.

For clients not yet supported by the wizard, or if you prefer editing config files by hand, see docs/manual-setup.md.

Agent Skills

Install reusable Canvas workflows into Claude Code, Cursor, GitHub Copilot, Cline, and 40+ other AI agents:

npx skills add bruchris/canvas-lms-mcp

Skill	Description
canvas-at-risk-students	Surface students with missing assignments or declining grades and send targeted outreach
canvas-gradebook-audit	Inspect the full grade-change audit trail — who changed what grade, when, and by how much
canvas-outcome-tracker	Track learning outcome mastery and class-wide proficiency for accreditation and program review

Skills are markdown workflow files (no extra dependencies). They work with the MCP server you already have installed. See the skills/ directory for the full list.

Example Prompts

Once configured, try these prompts with your AI client:

• "List all my active courses"
• "Show me the assignments for course 12345"
• "What's the average grade on the midterm exam?"
• "Grade Alice's essay submission with a B+ and add feedback"
• "Show me the rubric for the final project"
• "What discussions are happening in my Biology course?"
• "List all upcoming calendar events for course 12345"
• "Send a message to student 67890 about their missing assignment"

Tool Inventory

All Registered Tools (119)

Category	Tools
Health	health_check
Courses	list_courses, get_course, get_syllabus, create_course, update_course
Assignments	list_assignments, get_assignment, list_assignment_groups, create_assignment, update_assignment, delete_assignment
Submissions	list_submissions, get_submission, grade_submission, comment_on_submission
Rubrics	list_rubrics, get_rubric, get_rubric_assessment, submit_rubric_assessment
Quizzes	list_quizzes, get_quiz, list_quiz_submissions, list_quiz_questions, get_quiz_submission_answers, score_quiz_question
New Quizzes (LTI)	create_new_quiz, update_new_quiz, delete_new_quiz, list_new_quiz_items, get_new_quiz_item, create_new_quiz_item, update_new_quiz_item, delete_new_quiz_item
Files	list_files, list_folders, get_file, upload_file, delete_file
Gradebook History	list_gradebook_history_days, get_gradebook_history_day, list_gradebook_history_submissions, get_gradebook_history_feed
Users	list_students, get_user, get_profile, search_users, list_course_users
Groups	list_groups, list_group_members
Enrollments	list_enrollments, enroll_user, remove_enrollment
Discussions	, , , , , ,

84 tools are read-only and 35 tools perform Canvas write operations. When FERPA mode is enabled, resolve_pseudonym adds a 120th read tool.

All write tools require appropriate Canvas permissions. Canvas enforces its own permission model -- the MCP server does not bypass it.

Bulk operations

Canvas applies rate limits per-user. When creating many New Quizzes items (e.g., RAG-generated quizzes), call the tools serially rather than in parallel. For >50 items, chunk and pause between batches. If you hit a rate-limit error, wait a few seconds and retry.

MCP Resources (2)

Resource	URI Template	Type
Course Syllabus	canvas://course/{courseId}/syllabus	text/html
Assignment Description	canvas://course/{courseId}/assignment/{assignmentId}/description	text/html

Interactive widgets

view_course_structure is an MCP Apps tool: hosts that support the spec render an interactive tree explorer (collapsible modules, type-filter chips, title search, published/unpublished badges, links open in a new tab); hosts that don't fall back transparently to the same JSON payload that get_course_structure returns. The widget is self-contained — no external scripts, fonts, or network calls — and is shipped inline with the tool definition.

Tool	UI resource URI	Fallback
view_course_structure	ui://canvas-lms-mcp/course-structure.html	Same JSON payload as get_course_structure

Host verification (Claude Desktop, ChatGPT, Codex fallback) is performed manually after each release, since it requires real Canvas credentials. A screenshot will be added once the first verified host pass lands.

Deployment Modes

stdio (Default)

For local AI clients like Claude Desktop, Cursor, and VS Code. The server communicates over stdin/stdout.

npx canvas-lms-mcp --token $CANVAS_API_TOKEN --base-url $CANVAS_BASE_URL

HTTP

For web-based clients or hosted services. Starts an HTTP server with Streamable HTTP transport.

npx canvas-lms-mcp serve \
  --token $CANVAS_API_TOKEN \
  --base-url $CANVAS_BASE_URL \
  --port 3001 \
  --allowed-origin https://your-app.example.com

Endpoints:

• POST /mcp -- MCP protocol endpoint
• GET /health -- Health check (returns {"status":"ok"})

Docker

docker compose up -d

Requires CANVAS_API_TOKEN and CANVAS_BASE_URL environment variables. See docker-compose.yml.

services:
  canvas-lms-mcp:
    build: .
    ports:
      - "3001:3001"
    environment:
      - CANVAS_API_TOKEN=${CANVAS_API_TOKEN}
      - CANVAS_BASE_URL=${CANVAS_BASE_URL}

Library Import

Use the server factory directly in your own Node.js application:

import { createCanvasMCPServer } from 'canvas-lms-mcp'

const { server, canvas } = createCanvasMCPServer({
  token: userToken,
  baseUrl: canvasBaseUrl,
})

Or use the Canvas client standalone (no MCP dependency):

import { CanvasClient } from 'canvas-lms-mcp/canvas'

const canvas = new CanvasClient({
  token: userToken,
  baseUrl: canvasBaseUrl,
})

const courses = await canvas.courses.list()

CLI Reference

Flag	Env Variable	Default	Description
--token	`CANVAS_API_TOKEN