Canvas-MCP

# Canvas AI Assistant with MCP ## Overview This repository contains our project for building a **Model Context Protocol (MCP) server** that integrates with the **Canvas** learning management system (LMS). The goal is to provide an AI-driven assistant (e.g., Claude) with structured access to course information—assignments, due dates, lecture notes—so that it can help students stay organized and succeed academically. ## Getting Started # Mac: 0. Install `uv` if you haven't already: ```bash # if you're paranoid about piping to sh, go read the script by copy pasting the URL curl -LsSf https://astral.sh/uv/install.sh | sh ``` 1. Clone the repository: ```bash git clone https://github.com/AdityaPrakash-26/Canvas-MCP.git && cd Canvas-MCP ``` 2. Create the virtual environment: ```bash uv venv --seed ``` 3. Activate the virtual environment: ```bash source .venv/bin/activate ``` 4. Install the dependencies: ```bash uv sync ``` ## Installing to Claude Desktop If you don't have Claude Desktop MCP setup, you can follow the [Quickstart Guide](https://modelcontextprotocol.io/quickstart/user) to install it. To install this MCP server in Claude Desktop: 1. Open Claude Desktop 2. Go to Settings > Advanced > Edit Configuration 3. (MAC ONLY) Add the following to your `claude_desktop_config.json` file in the `tools` section: (it is a key under mcpServers) 4. (WINDOWS ONLY) See instructions below REPLACE $DIR with the absolute path to the directory where you cloned this repo. (MANDATORY!!!!!) REPLACE $DIR_uv with the uv path. (MANDATORY!!!!!) you can find it by running ```bash which uv ``` ```json "Canvas MCP": { "command": "$DIR_uv", "args": [ "run", "--with", "canvasapi>=3.3.0", "--with", "mcp[cli]", "--with", "python-dotenv>=1.0.1", "--with", "structlog>=24.1.0", "--directory", "$DIR", "src/canvas_mcp/server.py" ] } ``` # Windows We recommend using WSL (Windows Subsystem for Linux) to use this software. Installation instructions can be founder [here](https://learn.microsoft.com/en-us/windows/wsl/install). - Once installed, set up a new user in `/home/<username>` - Once you have the virtual environment setup, modify your claude desktop app config to include the following: ```json "Canvas MCP": { "command": "wsl.exe", "args": [ "-d", "Ubuntu", "--exec", "/home/<USER>/.local/bin/uv", "run", "--with", "canvasapi>=3.3.0", "--with", "mcp[cli]", "--with", "python-dotenv>=1.0.1", "--with", "structlog>=24.1.0", "--directory", "/home/<USER>/Canvas-MCP", "src/canvas_mcp/server.py" ] } ``` Replace `<USER>` with your username. ## Running To run the mcp command with uv: ```bash uv run mcp ``` ## Testing Alternatively, you can test it with the MCP Inspector: ```bash mcp dev src/canvas_mcp/server.py ``` ## Secrets Clone .env.example to .env and add your Canvas API key. Also change the variables in the .env file to match your Canvas instance. "CANVAS_API_KEY" "CANVAS_API_URL" --- ## Repository & Kanban - This **public GitHub repository** contains our code, documentation, and issues/tasks. - We maintain a **Kanban board** under the “Projects” tab with tasks from our roadmap for the first sprint. **Link to the Repo**: (https://github.com/AdityaPrakash-26/Canvas-MCP) **Link to the Kanban**: (https://github.com/users/AdityaPrakash-26/projects/1) --- ## License