图表MCP服务器

pip install -e .

pip install fastmcp plotly pandas kaleido pillow wordcloud matplotlib numpy

python src/main_optimized.py

data = [
    {"date": "12-17", "temperature": 5},
    {"date": "12-18", "temperature": 3},
    {"date": "12-19", "temperature": 2}
]

result = generate_line_chart(
    data=data,
    x_field="date",
    y_field="temperature",
    title="温度变化趋势"
)

data = [
    {"month": "1月", "sales": 120},
    {"month": "2月", "sales": 98},
    {"month": "3月", "sales": 145}
]

result = generate_column_chart(
    data=data,
    x_field="month",
    y_field="sales",
    title="月度销售额统计"
)

data = [
    {"category": "移动端", "value": 45},
    {"category": "桌面端", "value": 30},
    {"category": "平板", "value": 15}
]

result = generate_pie_chart(
    data=data,
    label_field="category",
    value_field="value",
    title="市场份额分布"
)

data = [
    {"month": "1月", "revenue": 120, "users": 1000},
    {"month": "2月", "revenue": 150, "users": 1200},
    {"month": "3月", "revenue": 180, "users": 1500}
]

result = generate_dual_axes_chart(
    data=data,
    x_field="month",
    y1_field="revenue",
    y2_field="users",
    title="收入与用户增长对比"
)

{
    "success": True,           # 是否成功
    "image_url": "http://127.0.0.1:8081/xxx.png", # 图像URL
    "message": "生成成功"       # 消息
}

{
    "success": False,
    "error": "错误信息"
}