by antvis
Effortlessly create 25+ chart types with MCP Server Chart. Visualize complex datasets using TypeScript and AntV for powe
Generate 25+ chart types (bar, line, pie, radar, Sankey, word cloud, etc.) using AntV visualization library. Creates interactive charts from data for analysis and presentation.
MCP Server Chart is a community-built MCP server published by antvis that provides AI assistants with tools and capabilities via the Model Context Protocol. Effortlessly create 25+ chart types with MCP Server Chart. Visualize complex datasets using TypeScript and AntV for powe It is categorized under analytics data. This server exposes 26 tools that AI clients can invoke during conversations and coding sessions.
You can install MCP Server Chart in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport. This server supports remote connections over HTTP, so no local installation is required.
MIT
MCP Server Chart is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
According to our notes, MCP Server Chart benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
MCP Server Chart is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
I recommend MCP Server Chart for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
MCP Server Chart reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired MCP Server Chart into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We evaluated MCP Server Chart against two servers with overlapping tools; this profile had the clearer scope statement.
MCP Server Chart is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Useful MCP listing: MCP Server Chart is the kind of server we cite when onboarding engineers to host + tool permissions.
MCP Server Chart is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
MCP Server Chart has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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A Model Context Protocol server for generating charts using AntV. We can use this mcp server for chart generation and data analysis.
<img width="768" alt="mcp-server-chart technical digram" src="https://mdn.alipayobjects.com/huamei_qa8qxu/afts/img/A*XVH-Srg-b9UAAAAAgGAAAAgAemJ7AQ/fmt.avif" />This is a TypeScript-based MCP server that provides chart generation capabilities. It allows you to create various types of charts through MCP tools. You can also use it in Dify.
Now 26+ charts supported.
<img width="768" alt="mcp-server-chart preview" src="https://mdn.alipayobjects.com/huamei_qa8qxu/afts/img/A*IyIRQIQHyKYAAAAAgCAAAAgAemJ7AQ/fmt.avif" />generate_area_chart: Generate an area chart, used to display the trend of data under a continuous independent variable, allowing observation of overall data trends.generate_bar_chart: Generate a bar chart, used to compare values across different categories, suitable for horizontal comparisons.generate_boxplot_chart: Generate a boxplot, used to display the distribution of data, including the median, quartiles, and outliers.generate_column_chart: Generate a column chart, used to compare values across different categories, suitable for vertical comparisons.generate_district_map - Generate a district-map, used to show administrative divisions and data distribution.generate_dual_axes_chart: Generate a dual-axes chart, used to display the relationship between two variables with different units or ranges.generate_fishbone_diagram: Generate a fishbone diagram, also known as an Ishikawa diagram, used to identify and display the root causes of a problem.generate_flow_diagram: Generate a flowchart, used to display the steps and sequence of a process.generate_funnel_chart: Generate a funnel chart, used to display data loss at different stages.generate_histogram_chart: Generate a histogram, used to display the distribution of data by dividing it into intervals and counting the number of data points in each interval.generate_line_chart: Generate a line chart, used to display the trend of data over time or another continuous variable.generate_liquid_chart: Generate a liquid chart, used to display the proportion of data, visually representing percentages in the form of water-filled spheres.generate_mind_map: Generate a mind-map, used to display thought processes and hierarchical information.generate_network_graph: Generate a network graph, used to display relationships and connections between nodes.generate_organization_chart: Generate an organizational chart, used to display the structure of an organization and personnel relationships.generate_path_map - Generate a path-map, used to display route planning results for POIs.generate_pie_chart: Generate a pie chart, used to display the proportion of data, dividing it into parts represented by sectors showing the percentage of each part.generate_pin_map - Generate a pin-map, used to show the distribution of POIs.generate_radar_chart: Generate a radar chart, used to display multi-dimensional data comprehensively, showing multiple dimensions in a radar-like format.generate_sankey_chart: Generate a sankey chart, used to display data flow and volume, representing the movement of data between different nodes in a Sankey-style format.generate_scatter_chart: Generate a scatter plot, used to display the relationship between two variables, showing data points as scattered dots on a coordinate system.generate_treemap_chart: Generate a treemap, used to display hierarchical data, showing data in rectangular forms where the size of rectangles represents the value of the data.generate_venn_chart: Generate a venn diagram, used to display relationships between sets, including intersections, unions, and differences.generate_violin_chart: Generate a violin plot, used to display the distribution of data, combining features of boxplots and density plots to provide a more detailed view of the data distribution.generate_word_cloud_chart: Generate a word-cloud, used to display the frequency of words in textual data, with font sizes indicating the frequency of each word.generate_spreadsheet: Generate a spreadsheet or pivot table for displaying tabular data. When 'rows' or 'values' fields are provided, it renders as a pivot table (cross-tabulation); otherwise, it renders as a regular table.[!NOTE] The above geographic visualization chart generation tool uses AMap service and currently only supports map generation within China.
To use with Desktop APP, such as Claude, VSCode, Cline, Cherry Studio, Cursor, and so on, add the MCP server config below. On Mac system:
{
"mcpServers": {
"mcp-server-chart": {
"command": "npx",
"args": ["-y", "@antv/mcp-server-chart"]
}
}
}
On Window system:
{
"mcpServers": {
"mcp-server-chart": {
"command": "cmd",
"args": ["/c", "npx", "-y", "@antv/mcp-server-chart"]
}
}
}
Also, you can use it on aliyun, modelscope, glama.ai, smithery.ai or others with HTTP, SSE Protocol.
If you are using an AI IDE with skill support (like Claude Code), you can use the chart-visualization skill to automatically select the best chart type and generate visualizations.
You can add the skill from https://github.com/antvis/chart-visualization-skills using:
npx skills add antvis/chart-visualization-skills
Then provide your data or describe the visualization you want. The skill will intelligently choose from 25+ chart types and generate the chart for you.
Install the package globally.
npm install -g @antv/mcp-server-chart
Run the server with your preferred transport option:
# For SSE transport (default endpoint: /sse)
mcp-server-chart --transport sse
# For Streamable transport with custom endpoint
mcp-server-chart --transport streamable
Then you can access the server at:
http://localhost:1122/ssehttp://localhost:1122/mcpEnter the docker directory.
cd docker
Deploy using docker-compose.
docker compose up -d
Then you can access the server at:
http://localhost:1123/ssehttp://localhost:1122/mcpYou can also use the following CLI options when running the MCP server. Command options by run cli with -H.
MCP Server Chart CLI
Options:
--transport, -t Specify the transport protocol: "stdio", "sse", or "streamable" (default: "stdio")
--host, -h Specify the host for SSE or streamable transport (default: localhost)
--port, -p Specify the port for SSE or streamable transport (default: 1122)
--endpoint, -e Specify the endpoint for the transport:
- For SSE: default is "/sse"
- For streamable: default is "/mcp"
--help, -H Show this help message
| Variable | Description | Default | Example |
|---|---|---|---|
VIS_REQUEST_SERVER | Custom chart generation service URL for private deployment | https://antv-studio.alipay.com/api/gpt-vis | https://your-server.com/api/chart |
SERVICE_ID | Service identifier for chart generation records | - | your-service-id-123 |
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.