# Antvis chart MCP server (`agentify/antvis-chart-mcp-server`) Actor

MCP server for generating charts using AntV. This server provides chart generation and data analysis capabilities with support for 25+ chart types including area, bar, line, pie, radar, scatter plots, maps, and specialized visualizations like treemaps, sankey diagrams, and word clouds.

- **URL**: https://apify.com/agentify/antvis-chart-mcp-server.md
- **Developed by:** [agentify](https://apify.com/agentify) (community)
- **Categories:** MCP servers, Automation, Open source
- **Stats:** 11 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### AntV Chart MCP Server

A Model Context Protocol server for generating charts using [AntV](https://github.com/antvis/). This server provides chart generation and data analysis capabilities with support for 25+ chart types including area, bar, line, pie, radar, scatter plots, maps, and specialized visualizations like treemaps, sankey diagrams, and word clouds.

**Chart Output:** All chart generation tools return direct links to high-quality PNG images of the generated charts, making them easy to view, share, and embed in documents or applications.

**About this MCP Server:** To understand how to connect to and utilize this MCP server, please refer to the official Model Context Protocol documentation at [mcp.apify.com](https://mcp.apify.com).

### Connection URL

MCP clients can connect to this server at:

```text
https://mcp-servers--antvis-chart-mcp-server.apify.actor/mcp
```

### Client Configuration

To connect to this MCP server, use the following configuration in your MCP client:

```json
{
  "mcpServers": {
    "antvis-chart": {
      "url": "https://mcp-servers--antvis-chart-mcp-server.apify.actor/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_APIFY_TOKEN"
      }
    }
  }
}
```

**Note:** Replace `YOUR_APIFY_TOKEN` with your actual Apify API token. You can find your token in the [Apify Console](https://console.apify.com/account/integrations).

### 🚩 Claim this MCP server

All credits to the original authors of <https://github.com/antvis/mcp-server-chart>

***

### ✨ Features

Now 25+ charts supported.

1. `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.
2. `generate_bar_chart`: Generate a `bar` chart, used to compare values across different categories, suitable for horizontal comparisons.
3. `generate_boxplot_chart`: Generate a `boxplot`, used to display the distribution of data, including the median, quartiles, and outliers.
4. `generate_column_chart`: Generate a `column` chart, used to compare values across different categories, suitable for vertical comparisons.
5. `generate_district_map` - Generate a `district-map`, used to show administrative divisions and data distribution.
6. `generate_dual_axes_chart`: Generate a `dual-axes` chart, used to display the relationship between two variables with different units or ranges.
7. `generate_fishbone_diagram`: Generate a `fishbone` diagram, also known as an Ishikawa diagram, used to identify and display the root causes of a problem.
8. `generate_flow_diagram`: Generate a `flowchart`, used to display the steps and sequence of a process.
9. `generate_funnel_chart`: Generate a `funnel` chart, used to display data loss at different stages.
10. `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.
11. `generate_line_chart`: Generate a `line` chart, used to display the trend of data over time or another continuous variable.
12. `generate_liquid_chart`: Generate a `liquid` chart, used to display the proportion of data, visually representing percentages in the form of water-filled spheres.
13. `generate_mind_map`: Generate a `mind-map`, used to display thought processes and hierarchical information.
14. `generate_network_graph`: Generate a `network` graph, used to display relationships and connections between nodes.
15. `generate_organization_chart`: Generate an `organizational` chart, used to display the structure of an organization and personnel relationships.
16. `generate_path_map` - Generate a `path-map`, used to display route planning results for POIs.
17. `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.
18. `generate_pin_map` - Generate a `pin-map`, used to show the distribution of POIs.
19. `generate_radar_chart`: Generate a `radar` chart, used to display multi-dimensional data comprehensively, showing multiple dimensions in a radar-like format.
20. `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.
21. `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.
22. `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.
23. `generate_venn_chart`: Generate a `venn` diagram, used to display relationships between sets, including intersections, unions, and differences.
24. `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.
25. `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.

> **Note:** The geographic visualization chart generation tools use [AMap service](https://lbs.amap.com/) and currently only support map generation within China.

### 🤖 Usage Examples

#### Generate a Simple Bar Chart

Ask the server to create a bar chart comparing sales data:

```
Generate a bar chart showing quarterly sales: Q1: 100, Q2: 150, Q3: 120, Q4: 180
```

#### Create a Line Chart for Time Series

```
Create a line chart showing website traffic over 6 months: Jan: 1000, Feb: 1200, Mar: 1100, Apr: 1400, May: 1600, Jun: 1500
```

#### Generate a Pie Chart for Distribution

```
Make a pie chart showing market share: Company A: 35%, Company B: 25%, Company C: 20%, Others: 20%
```

#### Create Advanced Visualizations

```
Generate a treemap showing product categories and their revenue contribution
Generate a sankey diagram showing customer journey from awareness to purchase
Create a radar chart comparing product features across multiple dimensions
```

### References

To learn more about Apify and Actors, take a look at the following resources:

- [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js)
- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Apify MCP Server](https://docs.apify.com/platform/integrations/mcp)
- [Webinar: Building and Monetizing MCP Servers on Apify](https://www.youtube.com/watch?v=w3AH3jIrXXo)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)

# Actor input Schema

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("agentify/antvis-chart-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("agentify/antvis-chart-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call agentify/antvis-chart-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=agentify/antvis-chart-mcp-server",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/A87rVwo8ztqfmiOOk/builds/nfdof7XW3Rrc2GAIw/openapi.json