Skip to main content
Glama

Canvas Assignment Assistant

by brendan-ch

Canvas Assignment Assistant MCP Server

Originally by mbcrosiersamuel.

Overview

This Model Context Protocol (MCP) server lets you interact with Canvas/Instructure courses and assignments, without leaving your LLM (e.g. Claude Desktop).

It allows you to retrieve, search, and summarize course and assignment information programmatically, for example to check due dates for upcoming assignments:

Due Dates

Features

Tools

  1. List Courses

    • Retrieve a list of courses

    • Filter by course state (active, completed, or all)

  2. Search Assignments

    • Search across courses for assignments

    • Filter by:

      • Search query

      • Due date range

      • Specific course

      • Include/exclude completed courses

  3. Get Assignment Details

    • Fetch detailed information about a specific assignment

    • Multiple output formats (full HTML, plain text, markdown)

Resources

  • Assignment Content: Retrieve full assignment details using a standardized URI format

Prerequisites

  • Node.js

  • Canvas LMS account

  • Canvas API Token

  • Canvas Domain

Environment Setup

Set the following environment variables:

  • CANVAS_API_TOKEN: Your Canvas API access token (see instructions below)

  • CANVAS_DOMAIN: Your Canvas institution's domain (e.g., canvas.youruniversity.edu)

How to Get Your Canvas API Token

  1. Log into Canvas

  2. Go to Account > Settings

  3. Scroll to the "Approved Integrations" section

  4. Click "New Access Token"

  5. Copy the generated token

For more details, see these instructions from Canvas.

Security Note

Keep your CANVAS_API_TOKEN confidential. Do not commit it to version control.

Installation

  1. Clone the repository and install dependencies

Clone the repository

git clone https://github.com/mbcrosier/canvas-mcp.git cd canvas-mcp

Install dependencies. If this throws an error, make sure you have node installed.

npm install
  1. Connect to the MCP server

    Copy the below json with the appropriate {{PATH}} values:

    { "mcpServers": { "canvas": { "command": "node", "args": ["/absolute/path/to/canvas-mcp/src/index.ts"], // cd into the src repo, run `pwd` and enter the output here "env": { "CANVAS_API_TOKEN": "your_api_token_here", "CANVAS_DOMAIN": "myschool.instructure.com" } } } }

    For Claude, save this as claude_desktop_config.json in your Claude Desktop configuration directory at:

    ~/Library/Application Support/Claude/claude_desktop_config.json

    For Cursor, save this as mcp.json in your Cursor configuration directory at:

    ~/.cursor/mcp.json
  2. Restart Claude Desktop / Cursor

    Open Claude Desktop and you should now see Canvas as an available integration.

    Or restart Cursor.

MCP Tools

  • list_courses: Shows all active courses by default. Use flags to show completed or all courses

  • search_assignments: Searches assignment titles and descriptions

  • get_assignment: Retrieves full assignment details

Troubleshooting

Common Issues

  • Token Invalid:

    • Regenerate your Canvas API token

    • Ensure token has appropriate permissions

  • Domain Incorrect:

    • Double-check your Canvas institution domain

    • Verify there are no typos

Disclaimer

This is an unofficial Canvas MCP, and is not affiliated with Canvas or Instructure. I'm also not a professional software engineer, and this project was vibe-coded using Claude, so please use it at your own risk :)

Thanks!

Deploy Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Enables interaction with Canvas LMS courses and assignments directly from your LLM, allowing you to retrieve, search, and summarize course information, check due dates, and access assignment details without leaving your AI assistant.

  1. Overview
    1. Features
      1. Tools
      2. Resources
    2. Prerequisites
      1. Environment Setup
        1. How to Get Your Canvas API Token
        2. Security Note
      2. Installation
        1. MCP Tools
          1. Troubleshooting
            1. Common Issues
          2. Disclaimer
            1. Thanks!

              MCP directory API

              We provide all the information about MCP servers via our MCP API.

              curl -X GET 'https://glama.ai/api/mcp/v1/servers/brendan-ch/canvas-mcp'

              If you have feedback or need assistance with the MCP directory API, please join our Discord server