Plotnine MCP Server
🎨 Discover a Model Context Protocol server that enables AI-driven data visualization with plotnine, merging ggplot2’s power with natural language interaction.
This grade comes from an automated MCPSafe scan of the server's JavaScript, TypeScript and Python source on 2026-10-02. It read the whole repository (13 files). It checks for leaked credentials, shell or code injection from function inputs, unsafe deserialization, malware signatures, install-time scripts, and weak password handling. It does not check for path traversal, server-side request forgery, prompt injection in tool descriptions, network exposure, SQL injection, cross-site scripting, or vulnerable dependencies. It has not been manually reviewed, and the code may have changed since the scan.
Excellent Security
Trust Score 80
Trust is stricter than security: it combines reviewed security, MCP capability risk, supply-chain metadata, quality, popularity, freshness, and penalties for unknowns.
- • No reviewed severe vulnerabilities published
- • Good documentation surface
- • Solid supply-chain metadata
- • Recently scanned
- • MCP risk traits: Filesystem access, Network/API access
Security ScoreA+
Vulnerabilities Found
Quality ScoreC
Maintenance58
Popularity3
Documentation100
Available Documentation
Compatibility72
Features
Supported Transports
Vulnerabilities(0)
This grade comes from an automated scan. Individual findings from automated scans are not published.
READMEPlotnine MCP Server
View source🎨 plotnine-mcp - Create Stunning Visuals Easily
🚀 Getting Started
Welcome to the plotnine-mcp project! This software helps you create high-quality statistical visualizations using Python. With plotnine, you can use a simple grammar to generate charts and graphs, making your data come alive. Whether you're a student or a professional, this tool can simplify your data visualization needs.
📥 Download the Software

To get started with plotnine-mcp, you need to download it from our Releases page. This page contains all the necessary files to run the application on your computer. You can find the link below:
- Download plotnine-mcp: Visit this page to download
💻 System Requirements
Before you download the software, ensure your computer meets the following requirements:
- Operating System: Windows 10 or later, macOS Mojave or later, or a recent version of Linux.
- Python: You need Python 3.7 or higher installed on your computer.
- Memory: At least 4 GB of RAM is recommended.
- Disk Space: Ensure you have at least 100 MB of free space.
🛠️ Installation Steps
Follow these steps to install plotnine-mcp on your machine:
- Download Software: Go to our Releases page.
- Select the Right File: Choose the version that fits your operating system. Common files include
.exefor Windows,.dmgfor macOS, and compressed files for Linux. - Run the Installer:
- For Windows: Double-click the downloaded .exe file.
- For macOS: Open the .dmg file, then drag the plotnine-mcp icon to the Applications folder.
- For Linux: Extract the compressed file and follow the included instructions.
- Launch the Application: After installation, find plotnine-mcp in your applications or search bar, and click to open.
🎨 Features
plotnine-mcp comes packed with features that make data visualization simpler:
- User-Friendly Interface: Easily navigate through options without technical knowledge.
- Natural Language Support: Use plain language to generate complex graphs.
- Compatibility: Works seamlessly with popular IDEs like Claude-Code, Cursor, and VSCode.
- Publication-Quality Visuals: Create visuals that meet publication standards without extensive graphic design skills.
📊 How to Use plotnine-mcp
Once you have installed plotnine-mcp, follow these steps to create your first visualization:
- Open the App: Launch the application from your applications menu.
- Load Your Data: Click the "Load Data" button to select your dataset. This can be in common formats like CSV or Excel.
- Choose a Visualization Type: Select the type of chart or graph you want to create from the menu.
- Enter Your Instructions: Use the natural language input box to describe your desired visual. For example, you can type "Show a bar chart of sales by month."
- Generate the Graph: Click the "Create" button to produce your visualization. You can then save or export your chart.
📋 Troubleshooting
If you encounter any issues while running plotnine-mcp, consider the following solutions:
- Installation Problems: Make sure your system meets the outlined requirements. If it does, try re-downloading and reinstalling the application.
- Performance Issues: If the application runs slowly, check if you have other resource-heavy applications open and close unnecessary ones.
- Data Loading Problems: Ensure your dataset is clean and in a supported format. Recheck your file path and dataset size.
For further help, you can also check the issues section of our GitHub repository.
🌐 Community and Support
Engage with the plotnine-mcp community for support and feedback:
- Issues Page: Report bugs or request features on our Issues page.
- Feature Suggestions: We welcome your ideas to improve the tool. Let us know what you'd like to see next!
✔️ License
plotnine-mcp is licensed under the MIT License. This allows you to use, modify, and distribute the software freely, as long as you include the original license.
Thank you for choosing plotnine-mcp. We look forward to seeing your visualizations!
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[](https://mcpsafe.org/registry/plotnine-mcp-server)Server Information
- Source
- GITHUB
- Language
- other
- License
- MIT
- Transport
- STDIO
- Added
- Aug 11, 2026
- Updated
- Oct 1, 2026