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Canvas MCP Server

@avarant

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT license

トランスポート

stdio

作者

avarant

Canvas MCP Server について

an mcp server for interacting with canvas

Canvas MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "canvas-mcp-server": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-r",
        "requirements.txt",
        "#",
        "Assuming",
        "a",
        "requirements.txt",
        "might",
        "be",
        "added",
        "later"
      ]
    }
  }
}

Canvas MCP Server のツール

5

Fetches the list of active courses for the current user.

Fetches the list of assignments for a specific course ID.

Fetches calendar events (assignments) for specified context codes (defaults to user).

Fetches upcoming calendar events (including assignments) for the user.

Fetches detailed information for a specific course ID.

概要

What is Canvas MCP Server?

A Canvas Model Context Protocol (MCP) server implemented in Python that exposes Canvas API functionalities as MCP tools using the canvas-lms-sdk. It is intended for users who want to programmatically interact with their Canvas LMS instance via MCP-compatible clients.

How to use Canvas MCP Server?

Set the CANVAS_API_URL and CANVAS_API_KEY environment variables with your Canvas credentials, install dependencies using uv (or pip) from the required repositories, then run python main.py. The server will start and listen for MCP client connections.

Key features of Canvas MCP Server?

  • Fetches active courses for the current user
  • Retrieves assignments for a specific course ID
  • Checks calendar due dates for specified context codes
  • Lists upcoming calendar events and assignments
  • Returns detailed information for a given course ID

Use cases of Canvas MCP Server?

  • Get an overview of all currently active courses
  • View assignments and due dates for a specific course
  • Check upcoming assignment deadlines on a calendar
  • Access detailed course information (e.g., syllabus, settings)
  • Automate Canvas data retrieval through MCP workflows

よくある質問

1

What are the prerequisites for running the server?

Python 3.8 or later, the `uv` package manager (or `pip`), and a Canvas API URL and API key from your institution.

2

How do I set up environment variables?

Export `CANVAS_API_URL` (e.g., `https://<your-institution>.instructure.com`) and `CANVAS_API_KEY` before running the server. For production, use a secure secret manager.

3

Which dependencies need to be installed?

The server requires `canvas-lms-sdk` (installed from a GitHub repository) and `mcp-sdk`. Install them via `uv pip install` or `pip` as shown in the README.

4

How do I start the server?

After setting environment variables and installing dependencies, run `python main.py` from the project directory.

5

What tools does the server currently provide?

Five tools: `get_active_courses`, `get_assignments_for_course`, `get_calendar_due_dates`, `get_upcoming_assignments`, and `get_class_information`.

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