Canvas MCP
Enables AI agents to interact with Canvas LMS and Gradescope, allowing users to query courses, assignments, modules, calendar events, and find relevant resources using natural language.
README
Canvas MCP
Canvas MCP is a set of tools that allows your AI agents to interact with Canvas LMS and Gradescope.


Features
- Find relevant resources - Ability to find relevant resources for a given query in natural language!
- Query upcoming assignments - Not only fetch upcoming assignments, but also provide its breakdown for a given course.
- Get courses and assignments from Gradescope - Query your Gradescope courses and assignments with natural language, get submission status, and more!
- Get courses
- Get modules
- Get module items
- Get file url
- Get calendar events
- Get assignments
- and so much more...
Usage
Note down the following beforehand:
- Canvas API Key from
Canvas > Account > Settings > Approved Integrations > New Access Token - Gradescope Email and Password https://www.gradescope.com/
Installing via Smithery (Preferred)
To install Canvas MCP for Claude Desktop via Smithery:
npx -y @smithery/cli install @aryankeluskar/canvas-mcp --client claude
Or, for Cursor IDE to use canvas-mcp with other models:
npx -y @smithery/cli install @aryankeluskar/canvas-mcp --client cursor
Or, for ChatGPT:
- Enable Developer Mode in settings, if not already enabled
- Go to
ChatGPT Settings > Connectorsand click Create to add this server URL:https://server.smithery.ai/@aryankeluskar/canvas-mcp/mcp
Manual Configuration (ONLY for local instances)
Create a .env file in the root directory with the following environment variables:
SNITHERY_API_KEY=your_snithery_api_key
Add the following to your mcp.json or claude_desktop_config.json file:
{
"mcpServers": {
"canvas": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"run",
"@aryankeluskar/canvas-mcp"
]
}
}
}
Built by Aryan Keluskar :)
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。