# Show HN: ProData AI – 14 MCP tools for automated data science

> Source: <https://mcpize.com/mcp/prodata-ai>
> Published: 2026-06-16 09:32:37+00:00

# ProData AI

Professional data analysis tool integrated with Claude's Model Context Protocol, featuring AutoML training, time series forecasting, dataset analysis, feature importance, and report generation.

## How to pay

### Subscribe

$9/month

Predictable monthly cost with included usage. Best for steady, high-volume traffic.

- Unlimited tools within plan limits
- One API key, billed once a month
- Cancel any time

[Overview](#overview)

ProData AI is a professional-grade automated data science platform integrated with Claude's Model Context Protocol. It delivers a complete end-to-end data pipeline — from raw CSV to cleaned data, ML models, forecasts, anomaly detection, clustering, correlation analysis, SQL generation, interactive dashboards, and AI-powered explanations — all in one server with 14 tools. No code required.

[Key Capabilities](#key-capabilities)

- analyze_dataset_tool: Performs full statistical profiling — mean, median, std, missing values, duplicates, and data quality score.
- train_automl_models_tool: Auto-trains and compares 6 ML models, returns the best performer with R² or accuracy score and feature importances.
- forecast_timeseries_tool: Prophet-powered time series forecasting with confidence intervals and MAPE validation score.
- get_feature_importance_tool: Identifies and ranks the top features driving your target variable using Random Forest.
- generate_report_tool: Compiles stats, ML results, data quality assessment, and recommendations into a comprehensive report.
- clean_dataset_tool: Automatically handles missing values, duplicates, whitespace, and outliers — returns a cleaned CSV with a full change log.
- detect_anomalies_tool: Flags outlier rows using Isolation Forest, Z-score, or IQR — returns anomaly scores and a clean CSV with anomalies removed.
- compare_datasets_tool: Side-by-side comparison of two CSVs — schema diff, statistical shifts, distribution changes, and an overall similarity verdict.
- cluster_data_tool: K-Means segmentation returning cluster profiles, sizes, and top distinguishing features. Ideal for customer segmentation.
- correlation_analysis_tool: Computes full correlation matrix with p-values, top correlated pairs, and multicollinearity warnings.
- explain_model_tool: Claude-powered plain-English explanation of ML results with business insights and actionable recommendations.
- generate_dashboard_tool: Returns a self-contained interactive HTML dashboard with KPI cards, line, bar, scatter, and doughnut charts.
- suggest_visualizations_tool: Analyzes column types and recommends the best chart types with rationale and column mappings.
- generate_sql_tool: Claude-powered natural language to SQL — describe what you want in plain English, get a ready-to-run query back.

[Use Cases](#use-cases)

- A supply chain manager uses forecast_timeseries_tool to predict inventory demand for the next quarter based on historical sales data.
- A fraud analyst uses detect_anomalies_tool with Isolation Forest to flag suspicious transactions in a financial dataset.
- A marketing analyst uses cluster_data_tool to segment customers by behavior and spending patterns.
- A data engineer uses clean_dataset_tool to fix missing values and remove duplicates before loading data into a pipeline.
- A business analyst uses explain_model_tool to get a plain-English ML summary for a boardroom presentation.
- A researcher uses compare_datasets_tool to detect data drift between last month's and this month's dataset before retraining a model.
- A developer uses generate_sql_tool to instantly convert plain English questions into ready-to-run SQL queries.
- A BI team uses generate_dashboard_tool to get an interactive HTML dashboard from any CSV in seconds.

[Who This Is For](#who-this-is-for)

This server is designed for data analysts, business analysts, data engineers, software developers, and technical researchers who need professional-grade data science outputs without building custom ML pipelines from scratch. Whether you need to clean data, train ML models, forecast trends, detect anomalies, segment customers, or generate dashboards — ProData AI handles the full pipeline in one MCP server. It is ideal for users familiar with CSV data structures who require immediate, evidence-based insights to inform their decision-making process. Compatible with Claude Desktop, Cursor, VS Code, Windsurf, and any MCP-compliant client.