For Developers

The Engine

Connect any AI agent to 40+ statistical analysis tools via the Model Context Protocol. One integration. Every analysis method. No code changes.

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Your Agent

One Config. Instant Access.

Add this to your MCP client configuration and restart.
That's the entire integration.

{
  "mcpServers": {
    "mcpanalytics": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote@latest",
        "https://api.mcpanalytics.ai/auth0"
      ]
    }
  }
}
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Settings > Developer > Edit Config
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Settings > MCP > Add Server
Other Clients
MCP configuration file

What Your Agent Gets

Instant access to a complete analytics toolkit through standardized MCP tools.

discover_tools

Semantic tool discovery

Find the right analysis tool using natural language. "I need to predict customer churn" returns ranked, compatible tools.

// Example call
discover_tools({
  query: "regression analysis",
  dataset_uuid: "ds_abc123"
})

datasets_upload / datasets_read

Secure data handling

Upload datasets securely with encryption. Read data with filtering, sampling, and column selection. All data encrypted at rest.

// Upload returns UUID + key
datasets_upload({
  prefix: "analysis"
})

tools_run

Execute any analysis

Run any statistical tool with automatic preprocessing, validation, and AI-generated insights. Returns shareable report URLs.

// Returns report URL
tools_run({
  tool_name: "linear_regression",
  taskList: { inputs: {...} }
})

reports_search / reports_list

Query past analyses

Search across all past reports with semantic queries. "What do we know about churn?" finds relevant insights from any analysis.

// Semantic search
reports_search({
  semantic_query: "profit margins"
})

40+ Statistical Tools

Professional-grade analysis methods, all accessible through the same interface.

Regression
  • Linear Regression
  • Ridge / Lasso
  • Elastic Net
  • Logistic
Time Series
  • ARIMA
  • Prophet
  • VAR
  • Exponential Smoothing
ML & Classification
  • Random Forest
  • XGBoost
  • K-Means Clustering
  • Decision Trees
Hypothesis Testing
  • T-Test
  • ANOVA
  • Chi-Square
  • Bayesian A/B
Customer Analytics
  • RFM Segmentation
  • CLV (BG/NBD)
  • Churn Prediction
  • Cohort Analysis
Causal Inference
  • Causal Impact
  • Diff-in-Diff
  • Propensity Matching
  • Synthetic Control
Economics
  • Price Elasticity
  • Demand Forecasting
  • Market Basket
  • Association Rules
Survival & Other
  • Cox Regression
  • Kaplan-Meier
  • PCA
  • Correlation
View All Tools

How It Works

The MCP protocol enables your agent to discover and execute tools autonomously.

1

Agent Gets Tools

MCP protocol exposes available tools to your agent

2

User Asks Question

"Analyze sales trends for Q4"

3

Agent Selects Tool

Discovers and calls appropriate analysis

4

Results Returned

Report URL + insights for the user

Example Agent Conversation
>
Can you analyze this sales data and predict next month's revenue?
*
datasets_upload {"prefix": "sales"}
UUID: ds_sales_12345, ready for analysis
*
discover_tools {"query": "forecast revenue", "dataset_uuid": "ds_sales_12345"}
Recommended: ARIMA (0.94), Prophet (0.91), Linear Regression (0.87)
*
tools_run {"tool_name": "arima", "taskList": {...}}
Report: https://api.mcpanalytics.ai/reports/arima_xyz123
*
Based on the ARIMA analysis, next month's projected revenue is $847,000 with a 95% confidence interval of $812K-$882K. The model detected strong seasonality...

Enterprise-Grade Security

Built for production. Secure by design.

OAuth 2.0 Authentication

Industry-standard authentication via Auth0. Secure token-based access with automatic refresh. No credentials stored in configs.

Encrypted Data Storage

All datasets encrypted at rest with AES-256. Client-side keys ensure only you can decrypt your data. Auto-expiration available.

Isolated Execution

Each analysis runs in an isolated Docker container. No cross-tenant data access. Automatic cleanup after completion.

Power Your Agent with Analytics

One config. 40+ tools. Instant statistical analysis for any AI agent.