canvas-mcp

MCP.Pizza Chef: r-huijts

Canvas MCP Server is a Model Context Protocol server designed to integrate AI assistants like Claude with Canvas LMS. It provides structured access to Canvas course management features including listing active courses, posting announcements, viewing rubrics, accessing student enrollment, and managing assignments and submissions. Built on Node.js, it requires a Canvas API token and instance URL for setup. This server empowers AI models to interact with Canvas LMS data in real-time, facilitating automated educational workflows and enhanced course administration.

Use This MCP server To

List active courses and details from Canvas LMS Post announcements to Canvas courses automatically Retrieve and display course rubrics for grading Access student enrollment and profile information Fetch assignment details and submission statuses View student submission history and instructor comments

README

Canvas MCP Server

A Model Context Protocol (MCP) server that enables AI assistants like Claude to interact with Canvas LMS. This server provides tools for managing courses, announcements, rubrics, assignments, and student data through the Canvas API.

Features

  • List active courses and their details
  • Post announcements to courses
  • View course rubrics
  • Get student enrollment information
  • Access assignment details and submissions
  • View student submission history and comments

Prerequisites

  • Node.js (v16 or higher)
  • A Canvas API token
  • Canvas instance URL (defaults to "https://fhict.instructure.com")

Installation

  1. Clone this repository and install dependencies:

    git clone <repository-url>
    cd canvas-mcp
    npm install
  2. Build the TypeScript project:

    npm run build
  3. Configure your environment variables:

    # Create a .env file
    echo "CANVAS_API_TOKEN=your_token_here" > .env
    # Optional: Set custom Canvas URL
    echo "CANVAS_DOMAIN=https://your-canvas-instance.com" >> .env

Claude Desktop Integration

  1. Open Claude Desktop's configuration file:

    MacOS:

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

    Windows:

    code %AppData%\Claude\claude_desktop_config.json
  2. Add the Canvas MCP server configuration:

    {
      "mcpServers": {
        "canvas": {
          "command": "node",
          "args": [
            "/path/to/canvas-mcp/build/index.js"
          ],
          "env": {
            "CANVAS_API_TOKEN": "your_token_here",
            "CANVAS_DOMAIN": "https://your-canvas-instance.com"
          }
        }
      }
    }
  3. Restart Claude Desktop to apply changes

Available Tools

list-courses

Lists all active courses for the authenticated user

  • No required parameters
  • Returns course names, IDs, and term information

post-announcement

Posts an announcement to a specific course

  • Required parameters:
    • courseId: string
    • title: string
    • message: string

list-rubrics

Lists all rubrics for a specific course

  • Required parameters:
    • courseId: string
  • Returns rubric titles, IDs, and descriptions

list-students

Gets a complete list of students enrolled in a course

  • Required parameters:
    • courseId: string
  • Optional parameters:
    • includeEmail: boolean (default: false)
  • Returns student names, IDs, and optional email addresses

list-assignments

Gets all assignments in a course with submission status

  • Required parameters:
    • courseId: string
  • Optional parameters:
    • studentId: string
    • includeSubmissionHistory: boolean (default: false)
  • Returns assignment details and submission status

list-assignment-submissions

Gets all student submissions for a specific assignment

  • Required parameters:
    • courseId: string
    • assignmentId: string
  • Optional parameters:
    • includeComments: boolean (default: true)
  • Returns submission details, grades, and comments

Available Prompts

analyze-rubric-statistics

Analyzes rubric statistics for formative assignments in a course and creates visualizations

  • Required parameters:
    • courseName: string (The name of the course to analyze)
  • Creates two comprehensive visualizations:
    1. Grouped stacked bar chart showing score distribution per criterion across all assignments
    2. Grouped bar chart showing average scores per criterion for all assignments
  • Provides comparative analysis across assignments and criteria
  • Includes progression analysis and trend identification

Troubleshooting

Common Issues

  1. Server not appearing in Claude Desktop:

    • Verify configuration file syntax
    • Check file paths are absolute
    • Ensure Canvas API token is valid
    • Restart Claude Desktop
  2. Connection errors:

    • Check Canvas API token permissions
    • Verify Canvas instance is accessible
    • Review Claude's MCP logs:
      # MacOS
      tail -f ~/Library/Logs/Claude/mcp*.log
      # Windows
      type %AppData%\Claude\Logs\mcp*.log

Debug Logging

The server logs errors to stderr. These can be viewed in Claude Desktop's logs or redirected when running manually:

node build/index.js 2> debug.log

Security Notes

  1. API Token Security:

    • Never commit your Canvas API token to version control
    • Use environment variables or secure configuration
    • Regularly rotate your API tokens
  2. Permissions:

    • Use tokens with minimum required permissions
    • Review Canvas API access logs periodically

License

MIT License

Copyright (c) 2024

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

canvas-mcp FAQ

How do I install the Canvas MCP server?
Clone the repository, install dependencies with npm, build the project, and configure environment variables including your Canvas API token and instance URL.
What are the prerequisites for running the Canvas MCP server?
You need Node.js v16 or higher, a valid Canvas API token, and the Canvas instance URL (default is https://fhict.instructure.com).
Can the Canvas MCP server post announcements to courses?
Yes, it supports posting announcements directly to Canvas courses via the API.
How does the Canvas MCP server handle student data?
It accesses student enrollment information, submission history, and comments securely through the Canvas API.
Is the Canvas MCP server compatible with multiple AI models?
Yes, it is designed to work with AI assistants like Claude, and can be integrated with other LLM providers such as OpenAI and Gemini.
How do I configure the Canvas instance URL?
You can set a custom Canvas instance URL in the .env configuration file; otherwise, it defaults to https://fhict.instructure.com.
What programming language is the Canvas MCP server built with?
The server is built using TypeScript and runs on Node.js.
Does the Canvas MCP server provide access to assignment submissions?
Yes, it allows viewing assignment details and student submissions through the Canvas API.