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by hustcc • Visualization & Charts
Generate Apache ECharts visualizations with an AI-driven MCP server that can export charts as images or option objects and optionally store outputs in MinIO.
Programmatically generate ECharts option objects and validated chart configurations for downstream rendering or editing.
Produce chart images (png/svg) or option exports and optionally upload/share them via MinIO-compatible object storage.
A locally-run, secure MCP server supporting stdio, SSE, or streamable transports for integrating chart generation into pipelines or desktop apps.
MCP ECharts is a lightweight, zero-dependency MCP server that generates ECharts options and renders charts (png/svg) using AI-driven workflows. It supports multiple transports (stdio, SSE, streamable), validates ECharts syntax, and can store chart images in MinIO or return Base64 data when MinIO is not configured. The server is designed for local, secure generation without relying on remote services and is easy to run via npm or as a global CLI.
Generate visual charts using Apache ECharts with echarts option and configuration dynamically. Apache ECharts is an Open Source JavaScript Visualization Library, which is used to create interactive charts and visualizations in web applications. It supports a wide range of chart types, including line charts, bar charts, pie charts, scatter plots, and more. ECharts is highly customizable and can be integrated with various data sources to create dynamic visualizations.
Generate an area chart to show data trends under continuous independent variables and observe the overall data trend, such as, displacement = velocity (average or instantaneous) × time: s = v × t. If the x-axis is time (t) and the y-axis is velocity (v) at each moment, an area chart allows you to observe the trend of velocity over time and infer the distance traveled by the area's size.
Generate a line chart to show trends over time, such as, the ratio of Apple computer sales to Apple's profits changed from 2000 to 2016.
Generate a bar chart to show data for numerical comparisons among different categories, such as, comparing categorical data and for horizontal comparisons.
Generate a pie chart to show the proportion of parts, such as, market share and budget allocation.
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