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Canvas MCP for Students

Welcome! This guide will help you set up Canvas MCP to use AI assistants as your personal Canvas helper.

What Can Canvas MCP Do for You?

Think of this as having an AI study buddy that knows everything about your Canvas courses:

  • Track assignments: "What's due this week?" - Get a complete view of deadlines
  • Monitor grades: "What's my current grade in all my courses?" - Stay on top of your performance
  • Manage peer reviews: "What peer reviews do I need to complete?" - Never miss a review
  • Access course content: "Show me the syllabus for BADM 350" - Quick access to pages and announcements
  • Check submission status: "Have I submitted everything?" - Know what's missing

Prerequisites

  • Python 3.10+ installed on your computer
  • MCP Client - Any MCP-compatible client:
  • Canvas Account at your university/institution

Installation

1. Clone the Repository

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

2. Install Dependencies

# Install uv package manager (faster than pip)
pip install uv

# Install Canvas MCP
uv pip install -e .

3. Get Your Canvas API Token

  1. Log in to your Canvas account
  2. Go to Account → Settings
  3. Scroll down to Approved Integrations
  4. Click + New Access Token
  5. Give it a purpose (e.g., "Claude AI Assistant")
  6. Click Generate Token
  7. Copy the token immediately - you won't see it again!

4. Configure Canvas MCP

Create a .env file in the canvas-mcp directory:

# Copy the template
cp env.template .env

# Edit the .env file and add your credentials

Your .env file should look like this:

# Canvas API Configuration
CANVAS_API_TOKEN=your_token_here
CANVAS_API_URL=https://canvas.youruniversity.edu/api/v1

# MCP Server Configuration (optional)
MCP_SERVER_NAME=canvas-mcp

# Privacy Settings (students don't need anonymization)
ENABLE_DATA_ANONYMIZATION=false

Important: Replace https://canvas.youruniversity.edu/api/v1 with your actual Canvas URL (including the /api/v1 suffix).

5. Configure Your MCP Client

Choose your MCP client and follow the appropriate configuration:

Claude Desktop (Recommended for beginners)

Configuration file location:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Add this configuration:

{
  "mcpServers": {
    "canvas-api": {
      "command": "/absolute/path/to/canvas-mcp/.venv/bin/canvas-mcp-server"
    }
  }
}

macOS path example: /Users/yourname/canvas-mcp/.venv/bin/canvas-mcp-server
Windows path example: C:\Users\yourname\canvas-mcp\.venv\Scripts\canvas-mcp-server.exe

Tip: Use the absolute path to the virtualenv binary so your client doesn't accidentally pick up a pyenv shim or other PATH entry.

Cursor

Configuration file location:

  • macOS/Linux: ~/.cursor/mcp_config.json
  • Windows: %USERPROFILE%\.cursor\mcp_config.json

Configuration:

{
  "mcpServers": {
    "canvas-api": {
      "command": "/absolute/path/to/canvas-mcp/.venv/bin/canvas-mcp-server"
    }
  }
}
Zed

Add to Zed's settings.json (Settings menu → Open Settings):

{
  "context_servers": {
    "canvas-api": {
      "command": {
        "path": "/absolute/path/to/canvas-mcp/.venv/bin/canvas-mcp-server",
        "args": []
      }
    }
  }
}
Windsurf IDE

Configuration file location:

  • macOS: ~/Library/Application Support/Windsurf/mcp_config.json
  • Windows: %APPDATA%\Windsurf\mcp_config.json

Configuration:

{
  "mcpServers": {
    "canvas-api": {
      "command": "/absolute/path/to/canvas-mcp/.venv/bin/canvas-mcp-server"
    }
  }
}
Continue

Add to Continue's config.json (Continue settings):

{
  "mcpServers": {
    "canvas-api": {
      "command": "/absolute/path/to/canvas-mcp/.venv/bin/canvas-mcp-server"
    }
  }
}
Other MCP Clients

For other MCP-compatible clients:

  1. Locate your client's MCP configuration file
  2. Add a server entry with the command path to canvas-mcp-server
  3. Restart your client

Consult your client's documentation for specific configuration format.

6. Test Your Setup

# Test the Canvas API connection
canvas-mcp-server --test

You should see: ✓ API connection successful!

7. Restart Your MCP Client

Close and reopen your MCP client to load the Canvas MCP server.

Verification:

  • Claude Desktop: Look for the 🔨 hammer icon when you start a conversation
  • Other clients: Check your client's documentation for how MCP tools are indicated

How to Use Canvas MCP

Quick Start Prompts

Try these prompts with your AI assistant:

Assignment Tracking:

  • "What assignments do I have due this week?"
  • "What's coming up in the next 3 days?"
  • "Show me my Canvas TODO list"

Grade Monitoring:

  • "What are my current grades in all my courses?"
  • "Show me my grades"
  • "How am I doing in BADM 350?"

Submission Status:

  • "Have I submitted all my assignments?"
  • "What haven't I turned in yet?"
  • "Show me my submission status for CSCI 101"

Peer Reviews:

  • "What peer reviews do I need to complete?"
  • "Show me my pending peer reviews"

Course Content:

  • "Show me the syllabus for BADM 350"
  • "What are the recent announcements?"
  • "What's on the homepage for my Marketing course?"

Discussions:

  • "What are the active discussions in HIST 202?"
  • "Show me recent posts in the Week 5 discussion"

Understanding Tool Calls

When you ask your AI assistant a question, it will use various "tools" to fetch data from Canvas. For example:

  • get_my_upcoming_assignments - Fetches your deadlines
  • get_my_course_grades - Gets your current grades
  • list_discussion_topics - Shows discussion forums
  • get_page_content - Retrieves course pages

Note: Different MCP clients may display tool usage differently. Claude Desktop shows a 🔨 icon when using tools.

Available Student Tools

Personal Organization

  • get_my_upcoming_assignments - View assignments due soon
  • get_my_todo_items - Your Canvas TODO list
  • get_my_submission_status - Check what you've submitted

Academic Performance

  • get_my_course_grades - Current grades across all courses

Peer Review Management

  • get_my_peer_reviews_todo - Peer reviews you need to complete

Course Content (Shared Tools)

  • list_courses - See all your enrolled courses
  • get_course_details - View syllabus and course info
  • list_pages - Access course pages
  • get_page_content - Read page content
  • list_announcements - See course announcements
  • list_discussion_topics - View discussion forums

Privacy & Security

Your Data Stays Private

  • Local only: Everything runs on your computer
  • Your data only: Tools access only YOUR Canvas data (not other students')
  • No external servers: No data sent anywhere except Canvas (via official API)
  • Canvas API security: Uses the same security as Canvas mobile app

Best Practices

  • Keep your API token secret - Don't share it or commit it to version control
  • Use a strong token purpose - Name it clearly so you can revoke it later if needed
  • Revoke if compromised - If you accidentally share your token, revoke it in Canvas settings

Troubleshooting

"Connection failed" or "Authentication error"

  • Check your Canvas API token is correct in .env
  • Verify your Canvas URL is correct (should match your browser's Canvas URL)
  • Make sure your token hasn't expired (some institutions have expiration policies)

"No tools appearing in your MCP client"

  • Restart your MCP client completely (Quit → Reopen)
  • Check canvas-mcp-server --test runs successfully
  • Verify your MCP client's configuration file is correct
  • For Claude Desktop: Check claude_desktop_config.json
  • For other clients: Consult your client's MCP configuration documentation

"No assignments/courses showing up"

  • Make sure you're enrolled in courses for the current term
  • Check if assignments have due dates set
  • Verify your Canvas account has the appropriate permissions

Need More Help?

Example Workflows

Morning Check-In

You: "Good morning! What do I need to focus on today?"

Your AI assistant will:
1. Check your upcoming assignments (next 24-48 hours)
2. Show any incomplete peer reviews
3. List recent announcements
4. Highlight your TODO items

Weekly Planning

You: "Help me plan my week"

Your AI assistant will:
1. Show all assignments due in the next 7 days
2. Identify which courses need attention
3. Check peer review deadlines
4. Summarize your current grade status

Before a Big Assignment

You: "I have a paper due Friday in ENGL 101. What do I need to know?"

Your AI assistant will:
1. Find the assignment details
2. Check if you've submitted
3. Show the rubric (if available)
4. Review peer review requirements (if applicable)

Tips for Best Results

  1. Be specific about courses: Use course codes (e.g., "BADM 350") when you can
  2. Ask follow-up questions: Your AI assistant remembers context within a conversation
  3. Request summaries: "Summarize my workload for next week"
  4. Combine requests: "Show me my grades and what's due this week"

What's Next?

Now that you're set up, explore what Canvas MCP can do! Try different prompts and see how your AI assistant can help streamline your academic workflow.

Happy studying! 📚