Labsco
timescale logo

Pylar

from timescale

Build custom MCP tools on any datasource and ship them to any agent builder from one control plane—using only SQL and a secure link.

🔥🔥🔥✓ VerifiedFreeQuick setup
#email#automation#crm#database#documents#devops#weather#security

Pylar Documentation

Build AI agents that interact with your data securely. Connect databases, create governed views, and deploy MCP tools to any agent builder.

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

  • Data Sources connect to Pylar (Snowflake, BigQuery, PostgreSQL, HubSpot, Salesforce, and more)

  • SQL View is created to govern exactly what data agents can access

  • MCP Tools are built on the view—multiple tools for different use cases

  • Tools publish to Agent Builders (Claude Desktop, Cursor, LangGraph, Zapier, Make, n8n, and more)

  • 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

Learn how Pylar provides governed SQL views, AI-powered MCP tool creation, and seamless multi-database integration.

Get up and running in minutes. Connect your databases, create views, and deploy your first agent.

Discover the benefits: security, developer experience, operational excellence, and cost efficiency.

See 20 real-world agent examples for customer support, sales, marketing, product, finance, and operations.

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.

Popular Use Cases

Build agents that access customer history, orders, and support tickets

Analyze pipeline, forecast revenue, and identify opportunities

Optimize campaigns, analyze attribution, and measure ROI

Track feature adoption, analyze usage patterns, and prioritize improvements

Analyze revenue, track expenses, and generate financial reports

Monitor system health, track performance, and generate incident reports

Documentation Sections

📚 Learn

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

  • Making Connections - Connect your data sources

  • Creating Data Views - Build governed SQL views

  • Building MCP Tools - Create tools for your agents

  • Publishing Tools - Deploy to agent builders

  • Connecting Agent Builders - Integrate with Claude, Cursor, LangGraph, and more

  • Evals - Monitor and optimize agent performance

💡 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)

See how others are using Pylar

❓ Help

Get answers to common questions and troubleshooting help:

  • FAQ - Frequently asked questions

  • Troubleshooting - Common issues and solutions

Need Help?

Ready to Get Started?

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