Canvas MCP Server

Canvas MCP Server

A remote MCP server for querying Canvas LMS courses, assignments, and grades. Enables natural language interaction with Canvas data via MCP clients like Claude Desktop.

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README

Canvas MCP Server

Read-only Remote MCP server (Streamable HTTP transport) for querying Canvas LMS courses, assignments, and grades.

Setup

  1. Install dependencies:

    npm install
    
  2. Configure Canvas credentials:

    cp .env.example .env
    

    Edit .env and add:

    • CANVAS_BASE_URL: Your Canvas instance URL (e.g., https://yourschool.instructure.com)
    • CANVAS_API_TOKEN: Your Canvas personal access token
    • CANVAS_TIMEOUT_MS (optional, default 15000): Timeout in milliseconds for outbound Canvas API requests (connect + read)
    • PORT (optional, default 8080): HTTP server port
    • BASE_PATH (optional, default /mcp): MCP endpoint path
    • ALLOWED_ORIGINS (optional): Comma-separated list of allowed origins for Origin validation (default: http://localhost:*,http://127.0.0.1:*)
    • MCP_AUTH_TOKEN (optional): If set, require Authorization: Bearer <token> on all /mcp requests (both GET and POST)

    To get your API token:

    • Log into Canvas
    • Go to Account → Settings
    • Scroll to "Approved Integrations"
    • Click "+ New Access Token"
    • Set purpose (e.g., "MCP Server"), leave expiry blank
    • Copy the token (you won't see it again!)
  3. Build the project:

    npm run build
    

Running the Server

Start the HTTP server:

npm run dev

The server will start on http://0.0.0.0:8080 (or your configured PORT) with:

  • MCP endpoint: http://localhost:8080/mcp
  • Health check: http://localhost:8080/healthz

Test health check:

curl http://localhost:8080/healthz

Expected response: OK

Note: The MCP endpoint (/mcp) uses Streamable HTTP transport (Server-Sent Events) and should be accessed by MCP clients (like Claude Desktop), not directly via curl.

Security & Ops Features:

  • Origin validation protects against unauthorized cross-origin requests
  • DNS rebinding protection validates the Host header
  • Supports localhost, private IP ranges (192.168.x.x, 10.x.x.x, 172.16-31.x.x), and .local domains (mDNS)
  • Configure allowed origins via ALLOWED_ORIGINS environment variable
  • Outbound Canvas API timeouts via CANVAS_TIMEOUT_MS (default 15000ms)
  • Structured per-request logging for every MCP tool call (never logs secrets)
  • Optional Bearer auth for /mcp endpoint using MCP_AUTH_TOKEN

MCP Auth (optional):

  • If MCP_AUTH_TOKEN is set, all /mcp requests must include header: Authorization: Bearer <token>
  • Auth is enforced after Host/Origin validation
  • On missing/invalid token, server returns 401 with { "error": "unauthorized" }
  • The token is never logged

Docker Deployment (Raspberry Pi / Production)

This project includes Docker support for production deployment on Raspberry Pi or any ARM/x64 system.

Prerequisites

  • Docker installed on your system
  • Docker Compose installed

Deployment Steps

  1. Clone the repository to your Raspberry Pi:

    git clone <your-repo-url>
    cd Canvas_MCP
    
  2. Create .env file with your Canvas credentials:

    cp .env.example .env
    nano .env
    

    Set your Canvas credentials:

    CANVAS_BASE_URL=https://yourschool.instructure.com
    CANVAS_API_TOKEN=your_canvas_api_token_here
    # Optional: outbound Canvas API timeout (ms)
    CANVAS_TIMEOUT_MS=15000
    # Optional: require Bearer token auth for /mcp
    MCP_AUTH_TOKEN=choose-a-strong-token
    
  3. Build and start the container:

    docker-compose up -d
    
  4. Verify the container is running:

    docker-compose ps
    
  5. Check logs:

    docker-compose logs -f
    
  6. Test the server:

    curl http://localhost:8080/healthz
    

Docker Compose Commands

Start the server:

docker-compose up -d

Stop the server:

docker-compose down

Restart the server:

docker-compose restart

View logs:

docker-compose logs -f canvas-mcp

Rebuild after code changes:

docker-compose down
docker-compose build --no-cache
docker-compose up -d

Configuration

The container automatically:

  • Restarts unless explicitly stopped (restart: unless-stopped)
  • Exposes port 8080
  • Includes health checks
  • Runs as non-root user for security

To change the port, edit docker-compose.yml:

ports:
  - "3000:8080"  # External:Internal

Connecting to Claude Desktop

This is a remote MCP server using Streamable HTTP transport. Configure Claude Desktop to connect to the running server.

Add to Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "canvas": {
      "url": "http://localhost:8080/mcp"
    }
  }
}

For Raspberry Pi or remote servers:

{
  "mcpServers": {
    "canvas": {
      "url": "http://raspberrypi.local:8080/mcp"
    }
  }
}

Or use the IP address:

{
  "mcpServers": {
    "canvas": {
      "url": "http://192.168.1.100:8080/mcp"
    }
  }
}

Important:

  1. The server must be running before starting Claude Desktop
  2. Start with Docker: docker-compose up -d or locally: npm run dev
  3. Verify the server is running: curl http://localhost:8080/healthz
  4. For remote connections, ensure port 8080 is accessible (firewall rules, etc.)

Restart Claude Desktop, then try:

  • "What Canvas courses am I enrolled in?"
  • "Show me assignments for [course name]"
  • "What assignments am I missing?"
  • "Check my submission status for [assignment name]"
  • "What's my current grade in [course name]?"
  • "What's due this week?"
  • "Show me all overdue assignments"

Current Features (v0.5)

list_courses

List all active Canvas courses with course ID, name, and course code.

list_assignments

List assignments for a specific course with details including:

  • Assignment ID, name, due date
  • Points possible, submission types
  • Submission status (workflow state, submitted date, missing/late flags)

Parameters:

  • course_id (required): The Canvas course ID
  • include_future (optional, default true): Include locked/future assignments. Best-effort filter based on unlock_at field; assignments without unlock_at are always included.
  • status_filter (optional, default "all"): Filter by submission status:
    • "all": No filtering (returns all assignments)
    • "missing": submission.missing === true OR (due date passed AND no submitted_at)
    • "unsubmitted": No submission object OR no submitted_at exists (regardless of due date)
    • "submitted": submitted_at exists OR workflow_state is submitted/graded

Supports pagination via Canvas Link headers.

get_submission_status

Get detailed submission status for a specific assignment with a single API request.

Returns:

  • assignment_id: The assignment ID
  • name: Assignment name
  • workflow_state: Current submission state (e.g., "unsubmitted", "submitted", "graded")
  • submitted_at: Submission timestamp (ISO 8601, null if not submitted)
  • graded_at: Grading timestamp (ISO 8601, null if not graded)
  • score: Numeric score (null if not graded)
  • late: Boolean flag indicating late submission
  • missing: Boolean flag indicating missing assignment
  • excused: Boolean flag indicating excused assignment

Parameters:

  • course_id (required): The Canvas course ID
  • assignment_id (required): The Canvas assignment ID

get_course_grades

Get grade summary for a course with graceful degradation. Single API request, read-only, never throws. Handles multiple enrollments by preferring active, most current enrollment.

Returns when grades are available:

{
  "course_id": 123456,
  "available": true,
  "current_score": 87.5,
  "current_grade": "B+",
  "final_score": 85.0,
  "final_grade": "B",
  "enrollment_state": "active",
  "term_id": 5678,
  "course_start_at": "2025-01-15T00:00:00Z",
  "course_end_at": "2025-05-15T00:00:00Z",
  "last_updated": null
}

Returns when grades not yet posted:

{
  "course_id": 123456,
  "available": false,
  "reason": "no_grades_yet",
  "enrollment_state": "active",
  "term_id": 5678,
  "course_start_at": "2025-01-15T00:00:00Z",
  "course_end_at": "2025-05-15T00:00:00Z"
}

Returns when grades are hidden or course not found:

{
  "course_id": 123456,
  "available": false,
  "reason": "hidden_or_unavailable"
}

Parameters:

  • course_id (required): The Canvas course ID

Behavior:

  • Handles multiple enrollments (e.g., retaking a course) by preferring enrollment_state="active" and the most current enrollment (by course end date or enrollment ID)
  • Distinguishes between grades not yet posted (no_grades_yet) and grades hidden/unavailable (hidden_or_unavailable)
  • Includes metadata for sanity-checking: enrollment_state, term_id, and course date range
  • All grade fields (scores, grades) may be null if not provided by Canvas
  • Never throws errors

list_upcoming

List upcoming and/or overdue assignments across all active courses in a single consolidated view. Reuses existing list_courses and list_assignments logic.

Example response:

[
  {
    "course_id": 123456,
    "course_name": "Introduction to Computer Science",
    "assignment_id": 789012,
    "name": "Homework 5",
    "due_at": "2025-01-12T23:59:00Z",
    "status": "unsubmitted",
    "points_possible": 100
  },
  {
    "course_id": 123456,
    "course_name": "Introduction to Computer Science",
    "assignment_id": 789013,
    "name": "Final Project",
    "due_at": "2025-01-20T23:59:00Z",
    "status": "submitted",
    "points_possible": 200
  }
]

Parameters:

  • days (optional, default 14): Number of days to look ahead for upcoming assignments
  • include_overdue (optional, default true): Include overdue assignments
  • course_ids (optional): Array of course IDs to filter. If not provided, checks all active courses.

Behavior:

  • Returns assignments due within the next N days and optionally overdue assignments
  • Sorted by due date ascending (overdue items appear first)
  • Status is one of: "submitted", "unsubmitted", "missing"
  • Skips assignments without due dates
  • Gracefully handles errors on individual courses (continues with remaining courses)

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