🤖 Parserator

The Structured Data Layer for AI Agents

Transform any unstructured input into agent-ready JSON with 95% accuracy. Built for Google ADK, MCP, LangChain, and any agent framework using our revolutionary two-stage Architect-Extractor pattern.

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🚀 Quick Start

Install & Use in 30 seconds

# Install globally
npm install -g parserator

# Parse any text instantly
parserator parse "Contact: John Doe, Email: john@example.com, Phone: 555-0123"

Output:

{
  "contact": "John Doe",
  "email": "john@example.com", 
  "phone": "555-0123"
}

Get API Access

# Get your free API key
curl -X POST https://parserator.com/api/keys/generate \
  -H "Content-Type: application/json" \
  -d '{"email": "your@email.com"}'

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🔧 Agent Integrations

Google ADK

@agent.tool
def extract_user_intent(user_message: str) -> UserIntent:
    return parse_for_agent(
        text=user_message,
        schema=UserIntent,
        context="command_parsing"
    )

MCP Server (Universal)

# Install MCP server for any agent
npm install -g parserator-mcp-server

# Use in any MCP-compatible agent
mcp://parserator/parse?schema=Contact&text=email_content

LangChain

from parserator import ParseChain

parser = ParseChain(api_key="your_key")
result = parser.parse(
    text="messy data here",
    output_schema={"name": "string", "age": "number"}
)

CrewAI

from parserator.integrations.crewai import ParseratorTool

parse_tool = ParseratorTool(
    name="extract_data",
    description="Parse unstructured text into JSON"
)

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⚡ Browser Extensions

Transform web data instantly while browsing:

Chrome Extension

• Status: Built and ready for Chrome Web Store submission
• Use: Right-click any text → "Parse with Parserator" → Perfect JSON
• Features: Auto-detect schemas, bulk export, local processing

VS Code Extension

• Status: Built and packaged (parserator-1.0.0.vsix)
• Use: Select messy data → Ctrl+Shift+P → Generate TypeScript types
• Features: Schema templates, batch processing, framework integration

Extensions will be published to official stores once API is finalized.

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🧠 How It Works: Architect-Extractor Pattern

Traditional LLMs waste tokens on complex reasoning with large datasets. Parserator uses a two-stage approach:

Stage 1: The Architect (Planning)

• Input: Your schema + small data sample (~1K chars)
• Job: Create detailed extraction plan
• LLM: Gemini 1.5 Flash (optimized for reasoning)
• Output: Structured search instructions

Stage 2: The Extractor (Execution)

• Input: Full dataset + extraction plan
• Job: Execute plan with minimal thinking
• LLM: Gemini 1.5 Flash (optimized for following instructions)
• Output: Clean, validated JSON

Results

• 70% token reduction vs single-LLM approaches
• 95% accuracy on complex data
• Sub-3 second response times
• No vendor lock-in - works with any LLM provider

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📦 Installation Options

🔹 Node.js/TypeScript

npm install parserator

🔹 Python

pip install parserator

🔹 Browser Extensions

• Chrome Extension: Built, pending Chrome Web Store submission
• VS Code Extension: Built, pending VS Code Marketplace submission

🔹 Agent Frameworks (In Development)

# MCP Server - Coming soon
npm install -g parserator-mcp-server

# Framework integrations - In beta
pip install parserator[langchain]
pip install parserator[crewai]
pip install parserator[adk]

Contact us for early access to framework integrations.

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🌟 Use Cases

For Developers

• API Integration: Parse inconsistent API responses
• Data Migration: Extract from legacy systems
• ETL Pipelines: Intelligent data transformation
• Web Scraping: Handle changing site layouts

For AI Agents

• Email Processing: Extract tasks, contacts, dates
• Document Analysis: Parse contracts, invoices, reports
• User Commands: Convert natural language to structured actions
• Research Workflows: Extract key info from papers, articles

For Data Teams

• Log Analysis: Structure unstructured log files
• Data Cleaning: Normalize messy datasets
• Import Processing: Handle varied file formats
• Quality Assurance: Validate data consistency

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🏗️ API Reference

Core Endpoint

POST https://api.parserator.com/v1/parse
Content-Type: application/json
Authorization: Bearer YOUR_API_KEY

{
  "inputData": "Contact: John Doe, Email: john@example.com, Phone: 555-0123",
  "outputSchema": {
    "contact": "string",
    "email": "string", 
    "phone": "string"
  },
  "instructions": "Extract contact information"
}

Response

{
  "success": true,
  "parsedData": {
    "contact": "John Doe",
    "email": "john@example.com",
    "phone": "555-0123"
  },
  "metadata": {
    "confidence": 0.96,
    "tokensUsed": 1250,
    "processingTimeMs": 800
  }
}

SDK Examples

JavaScript/TypeScript

import { Parserator } from 'parserator';

const parser = new Parserator('your-api-key');

const result = await parser.parse({
  inputData: 'messy text here',
  outputSchema: { name: 'string', age: 'number' }
});

console.log(result.parsedData);

Python

from parserator import Parserator

parser = Parserator('your-api-key')

result = parser.parse(
    input_data='messy text here',
    output_schema={'name': 'string', 'age': 'number'}
)

print(result.parsed_data)

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🏗️ Shared Core Architecture

Parserator uses a lean shared core architecture for maximum efficiency and maintainability:

Architecture Overview

┌─────────────────────────────────────────┐
│     SHARED CORE (@parserator/core)     │
│   Types, Validation, HTTP Client       │ 
└─────────────────────────────────────────┘
              │
     ┌────────┼────────┐
     │        │        │
┌────▼───┐ ┌──▼───┐ ┌──▼────────┐
│Node SDK│ │Python│ │Extensions │
│(50KB)  │ │ SDK  │ │ (Chrome,  │
│        │ │(50KB)│ │   VSCode) │
└────────┘ └──────┘ └───────────┘
     │        │        │
     └────────┼────────┘
              │
    ┌─────────▼─────────┐
    │  PRODUCTION API   │
    │ 95% Accuracy      │
    │ Architect-Extract │
    └───────────────────┘

Benefits

• 75% smaller SDK bundles (250KB vs 1MB total)
• Single source of truth for API logic
• Consistent experience across all platforms
• Faster maintenance and feature development

See SHARED_CORE_ARCHITECTURE.md for complete technical details.

🛡️ Exoditical Moral Architecture

Parserator is built on EMA principles - a revolutionary approach to ethical software development:

🔓 Digital Sovereignty

• Your data is yours - We never store input/output content
• No vendor lock-in - Export everything, switch anytime
• Open standards - JSON, OpenAPI, Docker - universal compatibility
• Transparent pricing - No hidden costs or usage surprises

🚪 The Right to Leave

• Complete data export - All schemas, templates, usage history
• Standard formats - Import into any compatible system
• Migration tools - Seamless transition to other platforms
• Zero retention - Data deleted immediately upon request

🌐 Universal Compatibility

• Framework agnostic - Works with any agent development platform
• LLM agnostic - Switch between OpenAI, Anthropic, Google, etc.
• Deployment agnostic - Cloud, on-premise, or hybrid
• Standard protocols - REST API, MCP, GraphQL support

"The ultimate expression of empowerment is the freedom to leave."

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🧪 Beta Program

🚀 Beta Features in Development

• Multi-LLM Support: Working on OpenAI, Anthropic, Google Gemini compatibility
• Schema Validation: Type checking and constraint enforcement
• Batch Processing: Handle multiple documents simultaneously
• Custom Workflows: Chain parsing operations
• Monitoring Dashboard: Parse analytics and performance metrics

Join the Beta

Contact us for beta access:

• Email: Gen-rl-millz@parserator.com
• Include: Your use case and which frameworks you're working with

Beta Feedback: GitHub Issues | GitHub Discussions

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📊 Pricing

Currently in beta - Contact us for early access pricing and custom solutions.

• Email: Gen-rl-millz@parserator.com
• Beta Program: Free access for early adopters and feedback providers

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🤝 Community & Support

📚 Documentation

• API Reference: Coming soon in docs/ directory
• Integration Guides: Available in this repository
• Examples: Check examples/ directory for framework integrations

💬 Community

• GitHub Issues: Bug reports and feature requests
• GitHub Discussions: Community questions and feedback
• YouTube: @parserator - Tutorials and demos coming soon
• LinkedIn: Company Page - Updates and announcements

🛠️ Support

• Email: Gen-rl-millz@parserator.com
• Response: We'll get back to you as soon as possible
• Beta Support: Priority support for early adopters

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🏆 Why Parserator?

Feature	Parserator	Traditional Parsers	Single-LLM Solutions
Accuracy	95%	60-70%	85%
Token Efficiency	70% less	N/A	Baseline
Setup Time	<5 minutes	Hours/Days	30 minutes
Maintenance	Zero	High	Medium
Vendor Lock-in	None	High	Medium
Schema Flexibility	Unlimited	Fixed	Limited

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📈 Development Status

Current Focus:

• ✅ Core parsing engine - Two-stage Architect-Extractor pattern
• ✅ Browser extensions - Chrome and VS Code extensions built
• ✅ Agent integrations - LangChain, CrewAI, Google ADK support
• 🚧 Documentation - API reference and integration guides in progress
• 🚧 Beta testing - Gathering feedback from early adopters

Planned Features:

• Multi-modal parsing (images, PDFs, audio)
• Enhanced schema validation and templates
• Enterprise deployment options
• Additional framework integrations

Roadmap details will be updated based on community feedback and beta testing results.

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📄 License

MIT License - see LICENSE file for details.

EMA Commitment: This project follows Exoditical Moral Architecture principles, ensuring your right to digital sovereignty and freedom to migrate.

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🙏 Credits

Built with radical conviction by GEN-RL-MiLLz - "The Higher Dimensional Solo Dev"

"Grateful for your support as I grow Hooves & a Horn, taking pole position for the 2026 Agentic Derby."

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🚀 Get Started • 📚 Documentation • 💬 Discord • 🐙 GitHub

Transform your messy data into agent-ready JSON today.