chartforge-data-mcp
v0.2.0
Published
MCP server for data preparation and transformation — parse CSV/JSON, clean datasets, compute aggregations, detect outliers, pivot tables, and prepare data for chart visualization with ChartForge
Maintainers
Readme
chartforge-data-mcp
MCP server for data preparation, cleaning, transformation, and statistical analysis — the essential first step before creating charts and visualizations with ChartForge.
Tools
| Tool | Description |
|------|-------------|
| parse_data | Parse CSV or JSON data and profile columns — types, null counts, unique values, samples |
| clean_data | Remove duplicates, handle missing values (drop/mean/median/mode/fill), normalize formats |
| analyze_data | Statistics for numeric columns — mean, median, std dev, percentiles, outlier detection, correlations |
| transform_data | Aggregate (group by + sum/avg/count), sort, filter, pivot, compute new columns, select/rename |
| suggest_chart | Recommend the best chart types based on your data structure and purpose |
Install
npx chartforge-data-mcpConfiguration
Claude Desktop
{
"mcpServers": {
"chartforge-data": {
"command": "npx",
"args": ["-y", "chartforge-data-mcp"]
}
}
}Examples
Parse and profile a dataset
parse_data({ data: "Month,Revenue,Expenses\nJan,45000,32000\nFeb,48000,33500\nMar,52000,35000" })Clean data with missing values
clean_data({ csv: "Name,Score\nAlice,95\nBob,\nCarol,88\nDave,null", missingStrategy: "median" })Aggregate by category
transform_data({ csv: "Region,Product,Sales\nNorth,A,100\nNorth,B,200\nSouth,A,150", operation: "aggregate", groupBy: "Region", valueColumn: "Sales", aggregation: "sum" })Get chart recommendations
suggest_chart({ csv: "Quarter,Revenue,Profit\nQ1,2.3M,0.5M\nQ2,2.8M,0.7M\nQ3,3.1M,0.8M\nQ4,3.9M,1.2M", purpose: "show revenue growth" })Related
- chartforge-generate-mcp — Generate charts from natural language
- chartforge-template-mcp — Chart templates and presets
- chartforge-analytics-mcp — Chart performance analytics
License
MIT
