Desmos-MCP

# Desmos-MCP Server --- English | [中文](./README.zh.md) --- This is a standard Model Context Protocol (MCP) server designed to provide powerful mathematical formula visualization and analysis capabilities for Large Language Models (LLMs). It utilizes `sympy` for local rendering and computation, and can optionally integrate with the Desmos API. ## ✨ Features - **Interactive Formula Validation**: Use the `validate_formula` tool to check the syntax of mathematical formulas. If a formula is invalid, it uses the LLM sampling feature to provide an easy-to-understand explanation of the error. - **Single Function Plotting**: Use the `plot_math_function` tool to generate a 2D plot from a formula. It supports using the Desmos API (configurable via `config.json`) or falling back to local `matplotlib` rendering, and provides progress reports during execution. - **Multiple Function Plotting**: Use the `plot_multiple_functions` tool to plot multiple functions on the same graph. - **Symbolic Analysis**: Use the `analyze_formula` tool to calculate mathematical properties of a formula, such as its domain, range, and critical points. - **Save Plot to File**: Automatically saves the generated plot as a PNG file to a `Desmos-MCP` folder on your desktop. ## ⚙️ Tech Stack - Python 3.10+ - FastMCP - Sympy - Matplotlib - HTTPX ## 🚀 Installation & Setup 1. **Clone the project** (if you haven't already) 2. **Install `uv`** If you don't have `uv` installed, run the following command in your terminal: ```sh powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" ``` 3. **Create a virtual environment** In the project root directory, run: ```sh uv venv ``` 4. **Install dependencies** ```sh uv sync ``` This command will install all the necessary dependencies based on the `pyproject.toml` file. ## 🔧 Configuration The server's behavior is controlled by the `config.json` file in the project root. ```json { "desmos": { "use_api": true, "api_key_env_var": "DESMOS_API_KEY", "fallback_to_local": true }, "rendering": { "default_width": 600, "default_height": 400 } } ``` - `desmos.use_api`: If `true`, the server will first attempt to use the Desmos API for plotting. - `desmos.api_key_env_var`: Specifies the name of the environment variable used to get the Desmos API key. - `desmos.fallback_to_local`: If `use_api` is `true` but the API call fails, this determines if the server should automatically fall back to local rendering. ### Set Desmos API Key (Optional) To use the Desmos API feature, you need to set an environment variable. For example, in PowerShell: ```powershell $env:DESMOS_API_KEY="your_actual_api_key_here" ``` ## ▶️ Running the Server To run the server independently for testing, execute the following command in the project root: ```sh uv run src/main.py ``` The server will start via standard input/output (stdio) and will be ready to be connected by an MCP client (like the Gemini CLI). ## 📝 To-Do - [ ] **Add 3D plotting support.** - [ ] **Implement real-time formula analysis and interactive plotting, similar to Desmos.** ## 📄 License This project is licensed under the Apache 2.0 License. See the [LICENSE](LICENSE) file for details.