A Model Context Protocol (MCP) server for data visualization. It exposes tools to render charts (line, bar, pie, scatter, heatmap, etc.) from data and returns the plot as image/base64 text/mermaid diagram.

Why MCP Plots?

• Instant, visual-first charts using Mermaid (renders directly in MCP clients like Cursor)
• Simple prompts to generate charts from plain data
• Zero-setup options via uvx, or install from PyPI/Docker
• Flexible output formats: mermaid (default), PNG image, or text

Quick Usage

• Ask your MCP client: "Create a bar chart showing sales: A=100, B=150, C=80"
• Default output is Mermaid, so diagrams render instantly in Cursor

Quick Start

PyPI Installation (Recommended)

pip install mcp-plots
mcp-plots  # Start the server

For Cursor Users

1. Install the package: pip install mcp-plots
2. Add to your Cursor MCP config (~/.cursor/mcp.json):

   {
     "mcpServers": {
       "plots": {
         "command": "mcp-plots",
         "args": ["--transport", "stdio"]
       }
     }
   }
   

   Alternative (zero-install via uvx + PyPI):

   {
     "mcpServers": {
       "plots": {
         "command": "uvx",
         "args": ["mcp-plots", "--transport", "stdio"]
       }
     }
   }
   

3. Restart Cursor
4. Ask: "Create a bar chart showing sales: A=100, B=150, C=80"

Development Installation

uvx --from git+https://github.com/mr901/mcp-plots.git run-server.py

Documentation → | Quick Start → | API Reference →

MCP Registry

This server is published under the MCP registry identifier io.github.MR901/mcp-plots. You can discover/verify it via the official registry API:

curl "https://registry.modelcontextprotocol.io/v0/servers?search=io.github.MR901/mcp-plots"

Registry metadata for this project is tracked in server.json.

Install with Smithery

This repository includes a smithery.yaml for easy setup with Smithery.

• File: smithery.yaml
• Docs: https://smithery.ai/docs/config#smitheryyaml

Example install using the Smithery CLI (adjust --client as needed, e.g. cursor, claude):

npx -y @smithery/cli install \
  https://raw.githubusercontent.com/mr901/mcp-plots/main/smithery.yaml \
  --client cursor

After installation, your MCP client should be able to start the server over stdio using the command defined in smithery.yaml.

Project layout

src/
  app/                # Server construction and runtime
    server.py
  capabilities/       # MCP tools and prompts
    tools.py
    prompts.py
  visualization/      # Plotting engines and configurations
    chart_config.py
    generator.py

Requirements

• Python 3.10+
• See requirements.txt

Setup Routes

uvx (Recommended)

The easiest way to run the MCP server without managing Python environments:

# Run directly with uvx (no installation needed)
uvx --from git+https://github.com/mr901/mcp-plots.git run-server.py

# Or insta

... [View full README on GitHub](https://github.com/mr901/mcp-plots#readme)