Canvas LMS MCP Server
Connects to the Canvas LMS API to manage and retrieve information about courses, assignments, grades, announcements, and files, while also supporting assignment submissions and messaging.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Canvas LMS MCP ServerWhat assignments are due in the next 7 days?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Canvas LMS MCP Server
An MCP (Model Context Protocol) server that connects Claude to the Canvas LMS API. Lets Claude read your courses, assignments, grades, announcements, files, and more — directly from Canvas.
Works remotely (hosted on Railway, no local setup) or locally (stdio transport for Claude Desktop).
Tools
Tool | Description |
| List all active courses |
| Assignments for a course (due dates, points, submission status) |
| Current grades for a course |
| Recent announcements for a course |
| Assignments due in the next N days across all courses |
| Submit a text-based assignment |
| List files in a course |
| Send a Canvas inbox message |
Quick Start — Remote (Recommended)
No installation needed. Just add this to your Claude Desktop config:
Windows: %APPDATA%\Claude\claude_desktop_config.json
Mac: ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"canvas-lms": {
"url": "https://YOUR_RAILWAY_URL/mcp",
"headers": {
"x-canvas-api-token": "YOUR_CANVAS_API_TOKEN",
"x-canvas-base-url": "https://canvas.yourschool.edu"
}
}
}
}Replace YOUR_RAILWAY_URL with the deployed server URL, and fill in your Canvas credentials.
Then restart Claude Desktop (fully quit, not just close the window).
Local Setup (Development)
1. Get a Canvas API Token
Log in to your Canvas instance (e.g.
https://canvas.yourschool.edu)Go to Account > Settings
Scroll to Approved Integrations
Click + New Access Token
Give it a name (e.g. "Claude MCP"), set expiry as desired, click Generate Token
Copy the token immediately — you won't be able to see it again
2. Clone and Install
git clone https://github.com/alexherman11/Canvas_MCP.git
cd Canvas_MCP
npm install3. Configure Credentials
cp .env.example .envEdit .env and fill in your values:
CANVAS_BASE_URL=https://canvas.yourschool.edu
CANVAS_API_TOKEN=your_token_here4. Test
node test.jsThis will:
Verify your Canvas API credentials work
Call each API endpoint
Start both the stdio and HTTP MCP servers and confirm they work
5. Register with Claude Desktop (Local)
{
"mcpServers": {
"canvas-lms": {
"command": "node",
"args": ["/absolute/path/to/Canvas_MCP/src/index.js"],
"env": {
"CANVAS_BASE_URL": "https://canvas.yourschool.edu",
"CANVAS_API_TOKEN": "your_token_here"
}
}
}
}Important: Replace the path in
argswith the absolute path tosrc/index.json your machine.
Self-Hosting on Railway
Fork this repo
Create a new project on Railway and connect your fork
Railway auto-detects Node.js — no Dockerfile needed
Optionally set
CANVAS_BASE_URLandCANVAS_API_TOKENin Railway's environment variables for single-tenant modeDeploy — the server starts on the assigned
PORTautomaticallyUse the Railway-provided URL in your Claude Desktop config (see Quick Start above)
The server exposes:
POST/GET/DELETE /mcp— MCP Streamable HTTP endpointGET /health— health check (returns200 OK)
Verify in Claude Desktop
After restarting, try asking Claude:
"What courses am I taking this quarter?"
"What assignments are due this week?"
"What's my grade in [course name]?"
Project Structure
Canvas_MCP/
src/
index.js — MCP server entry point (stdio transport, local dev)
server-http.js — MCP server entry point (HTTP transport, remote)
tools.js — All 8 tool definitions and handlers
canvas-api.js — Canvas REST API client (pagination, retries)
config.js — Environment configuration
test.js — Standalone test script
.env.example — Template for credentials
.gitignore — Excludes .env and node_modules
package.json
README.mdArchitecture
Remote mode:
Claude Desktop/claude.ai → HTTPS → Railway → Streamable HTTP → MCP server → Canvas API
↑
reads x-canvas-api-token &
x-canvas-base-url from headers
Local mode:
Claude Desktop → spawns process → stdio → MCP server → Canvas API
↑
reads CANVAS_API_TOKEN &
CANVAS_BASE_URL from env varsLicense
This server cannot be installed
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