makechartswithai
# Make Charts With AI — MCP Server
[](https://m8ven.ai/mcp/vickytr44-makechartswithai-mcp-1i3fke)
[](https://glama.ai/mcp/servers/vickytr44/makechartswithai-mcp)
[](https://glama.ai/mcp/servers/vickytr44/makechartswithai-mcp)
The **Make Charts With AI** MCP server exposes AI-powered chart recommendation and generation capabilities as standard [Model Context Protocol (MCP)](https://modelcontextprotocol.io) tools for AI agents — Claude Desktop, Cursor, Antigravity, VS Code, and more.
**npm package**: [`makechartswithai`](https://www.npmjs.com/package/makechartswithai)
---
## ⚡ Quick Start
### 1. Get an API Key
Visit [makechartswithai.online/mcp](https://makechartswithai.online/mcp) and generate a free anonymous API key (5 tool calls per key).
### 2. Add to Your MCP Client
Add the following to your MCP client configuration file (`claude_desktop_config.json`, `mcp_config.json`, etc.):
```json
{
"mcpServers": {
"makechartswithai": {
"command": "npx",
"args": ["-y", "makechartswithai"],
"env": {
"MAKECHARTSWITHAI_API_KEY": "mcwai_ak_your_key_here",
"MAKECHARTSWITHAI_BACKEND_URL": "https://makechartswithai.online"
}
}
}
}
```
That's it — your AI agent can now recommend and generate charts.
---
## 🛠️ Available MCP Tools
### 1. `recommend_charts`
Analyzes raw datasets (JSON, CSV, Markdown tables, or natural language prompts) and suggests optimal chart types with confidence scores and rationale.
**Inputs**:
- `dataset_json` (string, optional): Raw JSON data array or object string.
- `dataset_content` (string, optional): CSV, Markdown table, or plain text data.
- `user_intent` (string, optional): Natural language explanation of what you want to visualize.
- `focus_columns` (string[], optional): Target column names to prioritize.
---
### 2. `generate_chart`
Generates a production-ready chart specification and returns the output in your choice of format (`share_link`, `svg`, `png`). Rendering engine (`vegalite`, `echarts`, `chartjs`) is automatically determined based on chart type capabilities.
**Inputs**:
- `dataset_json` (string, optional): Raw JSON data string.
- `dataset_content` (string, optional): Tabular dataset (CSV, Markdown).
- `user_intent` (string, optional): Natural language visualization prompt.
- `preferred_chart_type` (string enum, optional): One of 46 supported chart types (`Bar Chart`, `Grouped Bar Chart`, `Stacked Bar Chart`, `Line Chart`, `Scatter Plot`, `Pie Chart`, `Area Chart`, `Heatmap`, `Radar Chart`, `Sunburst Chart`, `Sankey Diagram`, etc.).
- `output_format` (enum, optional: `"share_link"` | `"svg"` | `"png"`, default: `"share_link"`):
- `"share_link"`: Returns public view and edit URLs on [makechartswithai.online](https://makechartswithai.online).
- `"svg"`: Renders and returns vector SVG XML markup string.
- `"png"`: Renders and returns high-res PNG image payload (`image/png` base64 + saved file artifact).
---
## 🔑 Environment Variables
| Variable | Required | Description |
|---|---|---|
| `MAKECHARTSWITHAI_API_KEY` | ✅ | Your API key from [makechartswithai.online/mcp](https://makechartswithai.online/mcp) |
| `MAKECHARTSWITHAI_BACKEND_URL` | No | Backend URL (defaults to `https://makechartswithai.online`) |
---
## 📊 Supported Chart Types (46)
Area Chart, Bar Chart, Bar Table, Boxplot, Bubble Chart, Bullet Chart, Bump Chart, Calendar Heatmap, Candlestick Chart, Choropleth, Combo Chart, Connected Scatter Plot, Density Plot, Doughnut Chart, ECDF Plot, Funnel Chart, Gantt Chart, Gauge Chart, Grouped Bar Chart, Heatmap, Histogram, KPI Card, Line Chart, Lollipop Chart, Map, Network Graph, Parallel Coordinates, Pie Chart, Pyramid Chart, Radar Chart, Range Area Chart, Ranged Dot Plot, Regression, Rose Chart, Sankey Diagram, Scatter Plot, Slope Chart, Sparkline, Stacked Bar Chart, Streamgraph, Strip Plot, Sunburst Chart, Tree, Treemap, Violin Plot, Waterfall Chart.
---
## 🔗 Links
- 🌐 **App**: [makechartswithai.online](https://makechartswithai.online)
- 🔑 **API Keys**: [makechartswithai.online/mcp](https://makechartswithai.online/mcp)
- 📦 **npm**: [npmjs.com/package/makechartswithai](https://www.npmjs.com/package/makechartswithai)
- 🐙 **GitHub**: [github.com/vickytr44/makechartswithai-mcp](https://github.com/vickytr44/makechartswithai-mcp)
TDQS
Scored across 2 tools
recommend_charts and generate_chart have clearly distinct roles: one analyzes the dataset and suggests chart types, the other produces the actual chart artifact. There is no functional overlap, so an agent can confidently select the right tool.
Both tools follow the same verb_noun pattern with clear, action-first names. recommend_charts and generate_chart are predictable and easy to remember.
At only two tools, the server feels thin even though each tool covers an essential step. It is a minimal pipeline rather than a full-featured toolkit, which puts it in the borderline range.
The core recommend-then-generate workflow is covered with no dead ends. The main gap is lack of explicit refinement editing tools, but an agent can call generate again with adjusted parameters.