MCP数据可视化服务器配置依赖

# requirements.txt
# MCP数据可视化服务器依赖包

# 核心MCP包
mcp>=0.1.0

# 数据处理
pandas>=2.0.0
numpy>=1.24.0

# 可视化
matplotlib>=3.7.0
seaborn>=0.12.0

# 异步支持
asyncio-mqtt>=0.13.0

# JSON处理
jsonschema>=4.17.0

# 图像处理
Pillow>=9.5.0

# 可选：更多数据处理工具
scipy>=1.10.0
scikit-learn>=1.3.0

---

# config.json
# MCP服务器配置文件
{
   
  "server": {
   
    "name": "data-visualization",
    "version": "1.0.0",
    "description": "智能数据可视化MCP服务器",
    "capabilities": {
   
      "tools": true,
      "resources": false,
      "prompts": false
    }
  },
  "datasets": {
   
    "auto_load": true,
    "sample_data": true,
    "formats_supported": ["csv", "json", "excel"]
  },
  "visualization": {
   
    "default_style": "default",
    "figure_size": [12, 8],
    "dpi": 300,
    "formats": ["png", "svg", "pdf"]
  },
  "tools": {
   
    "list_available_datasets": {
   
      "enabled": true,
      "description": "列出所有可用数据集"
    },
    "get_dataset": {
   
      "enabled": true,
      "max_rows": 10000,
      "description": "获取数据集内容"
    },
    "analyze_data_structure": {
   
      "enabled": true,
      "include_statistics": true,
      "description": "分析数据结构和特征"
    },
    "suggest_visualization": {
   
      "enabled": true,
      "intelligent_selection": true,
      "description": "智能推荐可视化方案"
    },
    "create_chart": {
   
      "enabled": true,
      "supported_types": ["line", "bar", "scatter", "pie", "heatmap", "box"],
      "description": "创建数据可视化图表"
    },
    "get_data_insights": {
   
      "enabled": true,