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MCP Server for Generating Chart Image (FastMCP + FastAPI)

@qnnpnet

代码仓库

基本信息

分类

开发工具

传输方式

stdio

作者

qnnpnet

关于 MCP Server for Generating Chart Image

暂无概览

#chart-mcp#chart-generator#fastapi

MCP Server for Generating Chart Image 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "chart-mcp-server": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

MCP Server for Generating Chart Image 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Server for Generating Chart Image (FastMCP + FastAPI)?

This is an MCP server that generates chart images from Python plotting code. It converts Python code using matplotlib into a static PNG image and returns a URL to the saved file. It is built with FastMCP and FastAPI and intended for developers who need to programmatically generate charts from code snippets.

How to use MCP Server for Generating Chart Image (FastMCP + FastAPI)?

Clone the repository, install dependencies with uv sync, and run uv run main.py to start the server. The server listens on port 8107 by default. Send a POST request to /generate_chart with a JSON body containing the code field (Python code using matplotlib) to receive an image URL in the response.

Key features of MCP Server for Generating Chart Image (FastMCP + FastAPI)

  • Generates chart images from arbitrary matplotlib Python code
  • Returns a URL to the saved PNG image
  • Built on FastMCP and FastAPI for easy integration
  • Uses uv for dependency and environment management
  • Stores generated images in a static directory

Use cases of MCP Server for Generating Chart Image (FastMCP + FastAPI)

  • Embedding dynamic chart generation in AI assistant workflows
  • Converting text-based plotting instructions into shareable images
  • Automating chart creation from code snippets in applications
  • Serving as a tool inside MCP-based agents to produce visual outputs

常见问题

1

What are the runtime requirements?

Python 3.11 or higher is required. Dependencies include FastMCP, FastAPI, uvicorn, python-dotenv, requests, and matplotlib.

2

How do I start the server?

Clone the repository, run `uv sync` to install dependencies, then execute `uv run main.py`. The server will start on the default port.

3

How do I generate a chart?

Send a POST request to `http://localhost:8107/generate_chart` with a JSON body: `{"code": "import matplotlib.pyplot as plt\nplt.plot([1,2,3],[4,5,6])\nplt.title(\"My Chart\")"}`.

4

Where are the generated images stored?

Images are saved under `static/images/` with a timestamped filename. The response includes a full URL to access the image.

5

What does the response look like?

The response is a JSON object: `{ "image_url": "http://localhost:8107/static/images/20250419160332_d8b758e9.png" }`.

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