DataGen

Agentic synthetic data platform for schema design, AI generation, API automation, and MCP workflows.

From idea to production-ready data workflows in one screen

This guided showcase auto-scrolls through core capabilities: schema design, AI generation, API automation, MCP tools, and Web3-ready monetization.

Visual authoring

Drag-and-drop schema builder

  • 30+ field types with categories and drag targets
  • Per-field blanks, reorder, and schema validation
  • Preview, SQL, and multi-format export (CSV, XLSX, JSON, XML)

Design production-shaped tables without leaving the canvas.

Agentic AI

Natural language β†’ schema & samples

  • Topic or pasted examples to infer columns
  • Optional contract path: infer-schema β†’ validate β†’ generate-ai
  • SSE streaming and idempotent AI runs where enabled

Iterate fast with AI that respects structure and guardrails.

Developer ready

REST API & OpenAPI

  • /api/v1 health, capabilities, field-types, validate
  • Deterministic generate plus infer-schema / generate-ai
  • X-API-Key, machine-readable errors, downloadable .http samples

Wire agents and CI the same way you’d wire any first-party API.

MCP native

Tools, resources & prompts

  • stdio connector for local IDEs + hosted /mcp/sse
  • Same auth model as HTTP (X-API-Key)
  • Drop-in JSON configs for Cursor-style clients

Let assistants call DataGen as a first-class MCP server.

Web3 rails

x402 & Base Sepolia

  • Paid generation paths for autonomous agents
  • Escrow-aware flows and canary invoice samples
  • Monetized runbooks in-repo for API & MCP

Prototype machine-to-machine settlement without bolting on a second product.

πŸ€– AI-Powered
🎯 Drag & Drop Schema Builder
πŸ“Š Multi-Export (XLS, CSV, JSON, XML)
πŸ—„οΈ SQL Queries
πŸ’‘ Tip: Use drag & drop for quick schemas, or switch to AI Chat for natural language generation!

Field Types

Click category to expand/collapse, then drag fields

β–Ά Personal Data 6
πŸ‘€ First Name
πŸ‘€ Last Name
πŸ“§ Email
πŸ“± Phone
🏠 Address
πŸŽ‚ Birthdate
β–Ά Business Data 3
🏒 Company
πŸ’Ό Job Title
πŸ›οΈ Department
β–Ά Financial Data 12
πŸ’³ Credit Card
πŸ’° Currency
πŸ’΅ Amount
🏦 IBAN
πŸ“Š Account Number
πŸ“„ Invoice Number
🧾 Tax ID
πŸ“’ Ledger Code
🎯 Cost Center
πŸ”– Transaction ID
πŸ’Έ Transaction Amount
βœ… Payment Status
β–Ά Technical Data 4
πŸ”‘ UUID
🌐 IP Address
πŸ”— URL
πŸ‘¨β€πŸ’» Username
β–Ά Date & Time 3
πŸ“… Date
πŸ• DateTime
πŸŽ‚ Birthdate
β–Ά Numbers 3
πŸ”’ Integer
πŸ”’ Decimal
πŸ“Š Percentage

Your Schema

Field Name
Type
Options
Actions

Drag and drop fields here to build your schema

πŸ€–

Hello! I'm your AI assistant for generating synthetic data. Tell me what kind of data you need, and I'll create it for you.

Example: "I need customer data with 500 records including names, emails, phone numbers, and addresses"

OR

Generated Data Preview

HTTP API

Scripts, endpoints, and payloads

Production API base: https://datagen.gptlab.ae/api/v1
Auth header: X-API-Key: DATAGEN-...
Optional deduplication: Idempotency-Key for /generate-ai.

Core endpoints

  • GET /health
  • GET /capabilities
  • GET /field-types
  • POST /validate
  • POST /generate
  • POST /infer-schema
  • POST /generate-ai
  • POST /generate-ai/stream

Starter script (curl)

curl -X POST "https://datagen.gptlab.ae/api/v1/infer-schema" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: DATAGEN-FREE-REPLACE_ME" \
  -d '{"prompt":"payments dataset","field_count":8}'

Guarded AI generation

curl -X POST "https://datagen.gptlab.ae/api/v1/generate-ai" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: DATAGEN-FREE-REPLACE_ME" \
  -H "Idempotency-Key: ai-run-001" \
  -d '{"prompt":"payments dataset","record_count":100}'

Interactive CBDC / agentic series: Open the live walkthrough (blog β†’ built interactive).

MCP

Connection strings and MCP-ready configs

Hosted SSE endpoint: https://datagen.gptlab.ae/mcp/sse
Required header (paid/private tiers): X-API-Key: DATAGEN-...
Local stdio runner: python mcp_datagen/server.py.

Remote MCP config

{
  "server_url": "https://datagen.gptlab.ae/mcp/sse",
  "headers": {
    "X-API-Key": "DATAGEN-FREE-REPLACE_ME"
  }
}

Local stdio connection

DATAGEN_API_BASE=https://datagen.gptlab.ae
DATAGEN_API_KEY=DATAGEN-FREE-REPLACE_ME
python mcp_datagen/server.py

Tool groups exposed

  • health, catalog, capabilities
  • validate, generate
  • infer-schema, generate-ai, stream transcript
  • Resources: field-types, OpenAPI, capabilities

Interactive CBDC / agentic series: Open the live walkthrough (blog β†’ built interactive).

Generating data...