Pylar safely exposes structured data to AI agents by defining governed SQL views, generating MCP tools, and deploying controlled data access into any agent-building platform.
Pylar is a platform for giving AI agents safe, governed access to structured data across your organization. It focuses on making databases, warehouses, and other tabular data sources securely accessible to LLM-based agents without exposing raw schemas, sensitive fields, or unrestricted query capabilities. By sitting between your data infrastructure and agent builders, Pylar enables controlled, auditable data interactions that preserve both security and data quality.
At the core of Pylar is the ability to define governed SQL views that abstract away complex schemas and enforce row- and column-level restrictions. These views become the contract through which agents interact with data, ensuring every query respects organizational policies. Pylar also streamlines the creation of MCP (Model Context Protocol) tools, allowing you to package data operations—such as parameterized queries, lookups, and aggregations—into reusable, well-defined tools for any compatible agent platform. The system supports deployment to a range of agent builders, enabling consistent governance across multiple AI frameworks and runtime environments.
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