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Welcome to Pylar

Pylar is a secure data access layer for AI agents that enables interaction with structured data sources without requiring direct database access or complex API integrations.

How It Works

Pylar Workflow Diagram
  1. Data Sources connect to Pylar (Snowflake, BigQuery, PostgreSQL, HubSpot, Salesforce, and more)
  2. SQL View is created to govern exactly what data agents can access
  3. MCP Tools are built on the view—multiple tools for different use cases
  4. Tools publish to Agent Builders (Claude Desktop, Cursor, LangGraph, Zapier, Make, n8n, and more)
  5. Evals monitors all tool interactions for observability and optimization
Key Benefits:
  • Single Control Pane: Update views and tools without redeploying agents
  • No Raw Access: Agents only access data through your governed views
  • Unified Interface: One MCP endpoint for all data sources
  • Real-time Observability: Monitor all agent interactions with Evals

Key Features

🔒 Governed SQL Views

Create SQL views that define exactly what data agents can access. Views are the only access level—agents never get raw database access.

🤖 AI-Powered MCP Tool Creation

Describe what you want in natural language, and Pylar’s AI generates MCP tools for your agents. No manual coding required.

🔗 Multi-Database Integration

Join data across multiple databases, warehouses, and business applications. Query Snowflake, BigQuery, PostgreSQL, HubSpot, Salesforce, and more—all in one place.

📊 Built-in Observability

Monitor agent performance with the Evals dashboard. Track errors, query patterns, and optimize your tools based on real usage data.

🚀 One Control Pane

Update views and tools without redeploying agents. Changes reflect immediately across all agent builders—Claude Desktop, Cursor, LangGraph, Zapier, and more.

Getting Started

Step 1: Connect Your Data

Connect your databases and data sources to Pylar. Supported sources include:
  • Databases: BigQuery, Snowflake, PostgreSQL, MySQL, Redshift, MotherDuck, Supabase, and more
  • Business Apps: HubSpot, Salesforce, Google Sheets, and more

Making Connections

Learn how to connect your data sources

Step 2: Create Views

Use Pylar’s SQL IDE to create governed views of your data. Join across multiple databases, filter sensitive data, and define exactly what agents can access.

Creating Data Views

Learn how to create your first view

Step 3: Build MCP Tools

Create MCP tools using AI or manually. Each tool defines how agents interact with your views.

Building MCP Tools

Learn how to create MCP tools

Step 4: Publish and Deploy

Publish your tools and get your MCP credentials. Connect to any agent builder—no API hassles, no redeployment.

Publishing Tools

Learn how to publish and deploy your tools

Documentation Sections

📚 Learn

Comprehensive guides covering everything from connecting databases to monitoring with Evals:

💡 Examples

20 real-world agent examples across different domains:
  • Customer Support & Success (4 examples)
  • Sales & Revenue (4 examples)
  • Marketing (4 examples)
  • Product (3 examples)
  • Finance (3 examples)
  • Operations (2 examples)

Browse All Examples

See how others are using Pylar

❓ Help

Get answers to common questions and troubleshooting help:

Need Help?

Ready to Get Started?

Quick Start Guide

Follow our step-by-step guide to build your first agent