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

ProData AI, a professional automated data science platform integrated with Claude's Model Context Protocol, launched with 14 tools for tasks including AutoML training, time series forecasting, and report generation. The subscription-based service costs $9 per month and targets data analysts, engineers, and researchers seeking no-code data science capabilities.

read3 min views2 publishedJun 16, 2026

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 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

  • 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

  • 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 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 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.

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