ahnopologetic/canvas-lms-mcp

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A minimal Canvas LMS MCP (Machine Conversation Protocol) server for easy access to education data through your Canvas LMS instance.

概览

A minimal Canvas LMS MCP (Machine Conversation Protocol) server for easy access to education data through your Canvas LMS instance. This server provides a bridge between AI systems (like Cursor) and Canvas Learning Management System. - : List enrolled courses, get course details, syllabus, modules, and module items - : List and get assignments with optional submission status - : Get course pages by URL slug - : List your own submissions with grades and feedback - : List announcements across multiple courses - : List topics and view full discussion threads - : List calendar events with date filtering - : List planner items (assignments, announcements, etc.) - : Get enrollment data with grades - : List and get quizzes (classic quizzes only) - : List and get files - : Get course tabs, assignment groups, and favorite courses To install Canvas LMS Server for Claude Desktop automatically via Smithery: - Python 3.

README

以下为原文 README 节选，完整内容请查看原文。

Canvas LMS MCP Server

Features

Courses: List enrolled courses, get course details, syllabus, modules, and module items
Assignments: List and get assignments with optional submission status
Pages: Get course pages by URL slug
Submissions: List your own submissions with grades and feedback
Announcements: List announcements across multiple courses
Discussions: List topics and view full discussion threads
Calendar: List calendar events with date filtering
Planner: List planner items (assignments, announcements, etc.)
Enrollments: Get enrollment data with grades
Quizzes: List and get quizzes (classic quizzes only)
Files: List and get files
Navigation: Get course tabs, assignment groups, and favorite courses

Installation

Installing via Smithery

To install Canvas LMS Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @ahnopologetic/canvas-lms-mcp --client claude

Prerequisites

Python 3.13+
Canvas LMS API token
uv package manager (recommended)

Installation Methods

Option 1: Install with uvx (Recommended)

The easiest way to install and run canvas-lms-mcp is using uvx:

uvx canvas-lms-mcp

This will run the server in an isolated environment without installing it permanently.

To install the tool permanently:

uv tool install canvas-lms-mcp

Option 2: Install from Source

Clone the repository:

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

Install with uv:

# Install uv if you don't have it yet
curl -LsSf https://astral.sh/uv/install.sh | sh

# Create a virtual environment and install dependencies
uv venv
uv pip install -e .

Alternatively, use traditional methods:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -e .

Configuration

Set the following environment variables:

export CANVAS_API_TOKEN="your_canvas_api_token"
export CANVAS_BASE_URL="https://your-institution.instructure.com"  # Default: https://canvas.instructure.com

You can get your Canvas API token from your Canvas account settings.

Running the Server

Start the server with uv:

uv run src/canvas_lms_mcp/main.py

If installed with uvx tool:

canvas-lms-mcp

在 GitHub 查看完整 README

安装

uvx canvas-lms-mcp

新手？先看 mcpskill.org 教程 →

配置

{
    "mcpServers": {
        "canvas": {
            "command": "uvx",
            "args": ["canvas-lms-mcp"],
            "env": {
                "CANVAS_API_TOKEN": "your_canvas_api_token",
                "CANVAS_BASE_URL": "https://your-institution.instructure.com"
            }
        }
    }
}