Pylar

Pylar is a governed data access layer that sits between AI agents and your databases. Teams define what data agents can see by creating SQL views (or using natural language), which are automatically compiled into custom MCP tools. These tools can be published to any agent builder (Cursor, n8n, LangChain, etc.) with a single secure link, providing full observability across all AI deployments. It is designed for data, engineering, and ops teams that need to give AI agents safe, structured access to internal data without exposing raw databases. Pylar supports connecting multiple data sources (Snowflake, BigQuery, Postgres, HubSpot, Stripe, Zendesk, and 100+ managed connectors), joining data across them, and implementing row-level security and row-level filtering. Key differentiators include a visual SQL editor with AI-powered tool creation (type what you want, and Pylar generates the MCP tool), a publishing workflow that pushes tools to agent frameworks instantly, and an evals dashboard to monitor agent executions. Pylar also offers managed warehouses: if you don't have one, they can host your data by ingesting from business apps (CRM, support, marketing, finance) and syncing it to a Pylar-managed warehouse. Pricing is usage-based with four tiers: Starter ($20/mo, 5,000 executions), Team ($49/mo, 10,000 executions), Growth ($199/mo, 25,000 executions), and Enterprise (custom). A 14-day free trial with full access and no credit card is available. Compared to alternatives like Airplane or Retool, Pylar is purpose-built for AI agent data access, not general internal tools.