mcp-server-chart vs mcp-python-executor

Side-by-side comparison to help you pick between these two MCP servers.

	mcp-server-chart by antvis	mcp-python-executor by bsmi021
Stars	★ 4,068	★ 3
30d uses	10,239	—
Score	84	30
Official	—	—
Categories	AI / LLM ToolsDeveloper ToolsProductivity	Developer ToolsAI / LLM ToolsProductivity
Language	TypeScript	JavaScript
Last commit	this month	15 mo ago

mcp-server-chart · Summary

A TypeScript MCP server for generating 26+ visualization charts using AntV, supporting multiple chart types and deployment options.

mcp-python-executor · Summary

An MCP server for executing Python code and managing packages with safety constraints.

mcp-server-chart · Use cases

Data analysts creating visual reports from datasets
AI assistants generating custom charts based on user requests
Web applications embedding visualization capabilities via HTTP API

mcp-python-executor · Use cases

Data analysis workflows in AI assistants using Python libraries like pandas and numpy
Educational environments for teaching Python programming with safety constraints
Prototyping machine learning models in restricted execution environments

mcp-server-chart · Install

Installation

Install globally:

npm install -g @antv/mcp-server-chart

For Desktop Apps (e.g., Claude Desktop, VSCode):

{
  "mcpServers": {
    "mcp-server-chart": {
      "command": "npx",
      "args": ["-y", "@antv/mcp-server-chart"]
    }
  }
}

For Windows:

{
  "mcpServers": {
    "mcp-server-chart": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "@antv/mcp-server-chart"]
    }
  }
}

mcp-python-executor · Install

Installation

Clone the repository:

git clone https://github.com/bsmi021/mcp-python-executor.git
cd mcp-python-executor

Install dependencies:

npm install

Build the project:

npm run build

Configure in Claude Desktop:

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-python-executor": {
      "command": "node",
      "args": ["path/to/python-executor/build/index.js"],
      "env": {
        "PREINSTALLED_PACKAGES": "numpy pandas matplotlib scikit-learn",
        "MAX_MEMORY_MB": "512",
        "EXECUTION_TIMEOUT_MS": "30000",
        "MAX_CONCURRENT_EXECUTIONS": "5",
        "LOG_LEVEL": "info",
        "LOG_FORMAT": "json"
      }
    }
  }
}

Comparison generated from public README + GitHub signals. Last updated automatically.