mcp server
mcp-server-chart
A Model Context Protocol server for generating charts using AntV.
Description as published by the maintainer. Source
- version 1.0.0
- slowing
slowing — Most recent push to the repository was 2026-05-06.
What this server can do
25 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
generate_area_chart(data, stack, style, theme, title, width, height, axisXTitle, axisYTitle)- Generate a 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. Required: data.
generate_bar_chart(data, group, stack, style, theme, title, width, height, axisXTitle, axisYTitle)- Generate a horizontal bar chart to show data for numerical comparisons among different categories, such as, comparing categorical data and for horizontal comparisons. Required: data.
generate_boxplot_chart(data, style, theme, title, width, height, axisXTitle, axisYTitle)- Generate a boxplot chart to show data for statistical summaries among different categories, such as, comparing the distribution of data points across categories. Required: data.
generate_column_chart(data, group, stack, style, theme, title, width, height, axisXTitle, axisYTitle)- Generate a column chart, which are best for comparing categorical data, such as, when values are close, column charts are preferable because our eyes are better at judging height than other visual elements like area or angles. Required: data.
generate_district_map(data, title, width, height)- Generates regional distribution maps, which are usually used to show the administrative divisions and coverage of a dataset. It is not suitable for showing the distribution of specific locations, such as urban administrative divisions, GDP distribution maps of provinces and cities across the country, etc. This tool is limited to generating data maps within China. Required: title, data.
generate_dual_axes_chart(style, theme, title, width, height, series, axisXTitle, categories)- Generate a dual axes chart which is a combination chart that integrates two different chart types, typically combining a bar chart with a line chart to display both the trend and comparison of data, such as, the trend of sales and profit over time. Required: categories, series.
generate_fishbone_diagram(data, style, theme, width, height)- Generate a fishbone diagram chart to uses a fish skeleton, like structure to display the causes or effects of a core problem, with the problem as the fish head and the causes/effects as the fish bones. It suits problems that can be split into multiple related factors. Required: data.
generate_flow_diagram(data, style, theme, width, height)- Generate a flow diagram chart to show the steps and decision points of a process or system, such as, scenarios requiring linear process presentation. Required: data.
generate_funnel_chart(data, style, theme, title, width, height)- Generate a funnel chart to visualize the progressive reduction of data as it passes through stages, such as, the conversion rates of users from visiting a website to completing a purchase. Required: data.
generate_histogram_chart(data, style, theme, title, width, height, binNumber, axisXTitle, axisYTitle)- Generate a histogram chart to show the frequency of data points within a certain range. It can observe data distribution, such as, normal and skewed distributions, and identify data concentration areas and extreme points. Required: data.
generate_line_chart(data, stack, style, theme, title, width, height, axisXTitle, axisYTitle)- 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. Required: data.
generate_liquid_chart(shape, style, theme, title, width, height, percent)- Generate a liquid chart to visualize a single value as a percentage, such as, the current occupancy rate of a reservoir or the completion percentage of a project. Required: percent.
generate_mind_map(data, style, theme, width, height)- Generate a mind map chart to organizes and presents information in a hierarchical structure with branches radiating from a central topic, such as, a diagram showing the relationship between a main topic and its subtopics. Required: data.
generate_network_graph(data, style, theme, width, height)- Generate a network graph chart to show relationships (edges) between entities (nodes), such as, relationships between people in social networks. Required: data.
generate_organization_chart(data, style, theme, width, height, orient)- Generate an organization chart to visualize the hierarchical structure of an organization, such as, a diagram showing the relationship between a CEO and their direct reports. Required: data.
generate_path_map(data, title, width, height)- Generate a route map to display the user's planned route, such as travel guide routes. Required: title, data.
generate_pie_chart(data, style, theme, title, width, height, innerRadius)- Generate a pie chart to show the proportion of parts, such as, market share and budget allocation. Required: data.
generate_pin_map(data, title, width, height, markerPopup)- Generate a point map to display the location and distribution of point data on the map, such as the location distribution of attractions, hospitals, supermarkets, etc. Required: title, data.
generate_radar_chart(data, style, theme, title, width, height)- Generate a radar chart to display multidimensional data (four dimensions or more), such as, evaluate Huawei and Apple phones in terms of five dimensions: ease of use, functionality, camera, benchmark scores, and battery life. Required: data.
generate_sankey_chart(data, style, theme, title, width, height, nodeAlign)- Generate a sankey chart to visualize the flow of data between different stages or categories, such as, the user journey from landing on a page to completing a purchase. Required: data.
generate_scatter_chart(data, style, theme, title, width, height, axisXTitle, axisYTitle)- Generate a scatter chart to show the relationship between two variables, helps discover their relationship or trends, such as, the strength of correlation, data distribution patterns. Required: data.
generate_treemap_chart(data, style, theme, title, width, height)- Generate a treemap chart to display hierarchical data and can intuitively show comparisons between items at the same level, such as, show disk space usage with treemap. Required: data.
generate_venn_chart(data, style, theme, title, width, height)- Generate a Venn diagram to visualize the relationships between different sets, showing how they intersect and overlap, such as the commonalities and differences between various groups. Required: data.
generate_violin_chart(data, style, theme, title, width, height, axisXTitle, axisYTitle)- Generate a violin chart to show data for statistical summaries among different categories, such as, comparing the distribution of data points across categories. Required: data.
generate_word_cloud_chart(data, style, theme, title, width, height)- Generate a word cloud chart to show word frequency or weight through text size variation, such as, analyzing common words in social media, reviews, or feedback. Required: data.
Last successful function declaration observed on
.
Source: pkg:npm/@antv/mcp-server-chart. We list what the server declared;
we do not call any of these functions.
Endpoint status observed on
.
Source: pkg:npm/@antv/mcp-server-chart.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 4,289 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-05-06 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 16 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2025-09-15 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2025-09-15 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 25 tools | Number of functions the server declared when started and asked to list them. It says what the server offers an agent, not how well any of it works. | as of probe | npm |
|
| mcp endpoint status | ok | The server listed 25 functions when asked. | as of probe | npm |
|
| package install scripts | prepare | This package runs its own code during installation (prepare), before you ever start it. That is normal for many packages and is also where npm supply-chain attacks operate. We installed it with those scripts disabled. | as of probe | npm |
Where to get it
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These share tags the maintainers applied themselves, such as visualization. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: antv, llm, mcp, mcp-server, skills, visualization.
This record as data
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