Canvas MCP - 大学和高中课程

帆布 MCP

Canvas MCP 是一套工具，允许您的 AI 代理与 Canvas LMS 和 Gradescope 进行交互。

等级范围

特征

查找相关资源- 能够使用自然语言查找给定查询的相关资源！
查询即将到来的作业- 不仅获取即将到来的作业，还提供给定课程的细目分类。
从 Gradescope 获取课程和作业- 使用自然语言查询您的 Gradescope 课程和作业，获取提交状态等等！
获取课程
获取模块
获取模块项
获取文件 URL
获取日历事件
获取作业
还有更多...

用法

事先记下以下事项：

Canvas API 密钥来自Canvas > Account > Settings > Approved Integrations > New Access Token
Gemini API 密钥来自https://aistudio.google.com/app/apikey
Gradescope 电子邮件和密码https://www.gradescope.com/

通过 Smithery 安装（首选）

要通过Smithery自动为 Claude Desktop 安装 Canvas MCP：

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

或者，对于 Cursor IDE，将 canvas-mcp 与其他模型一起使用：

npx -y @smithery/cli install @aryankeluskar/canvas-mcp --client cursor

或者，对于 Windsurf：

npx -y @smithery/cli install @aryankeluskar/canvas-mcp --client windsurf

手动安装（仅适用于本地实例）

下载存储库并运行以下命令：

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

# Install dependencies with uv (recommended)
pip install uv
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -r requirements.txt

# Or install with pip
pip install -r requirements.txt

手动配置

在根目录中创建一个.env文件，其中包含以下环境变量：

CANVAS_API_KEY=your_canvas_api_key
GEMINI_API_KEY=your_gemini_api_key

将以下内容添加到您的mcp.json或claude_desktop_config.json文件中：

{
  "mcpServers": {
      "canvas": {
          "command": "uv",
          "args": [
              "--directory",
              "/Users/aryank/Developer/canvas-mcp",
              "run",
              "canvas.py"
          ]
      }
  }
}

由Aryan Keluskar建造 :)

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

一组使 AI 代理能够与 Canvas LMS 交互的工具，允许用户查找相关资源、获取课程信息并通过自然语言查询浏览模块。

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Canvas MCP - College and High School Courses

帆布 MCP

特征

用法

通过 Smithery 安装（首选）

手动安装（仅适用于本地实例）

手动配置

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