Canvas LMS MCP Server
Enables Claude to interact with the Canvas LMS API to manage courses, assignments, grades, and communications. It supports both remote and local deployments, allowing users to query academic data and submit assignments via natural language.
README
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 |
|---|---|
canvas_get_courses |
List all active courses |
canvas_get_assignments |
Assignments for a course (due dates, points, submission status) |
canvas_get_grades |
Current grades for a course |
canvas_get_announcements |
Recent announcements for a course |
canvas_get_upcoming_due |
Assignments due in the next N days across all courses |
canvas_submit_text_entry |
Submit a text-based assignment |
canvas_get_course_files |
List files in a course |
canvas_send_message |
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 install
3. Configure Credentials
cp .env.example .env
Edit .env and fill in your values:
CANVAS_BASE_URL=https://canvas.yourschool.edu
CANVAS_API_TOKEN=your_token_here
4. Test
node test.js
This 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 mode - Deploy — the server starts on the assigned
PORTautomatically - Use 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.md
Architecture
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 vars
License
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.