Wren Engine is a semantic engine designed for MCP clients and AI agents, enabling accurate data understanding and retrieval within complex enterprise environments, including trusted calculations and reporting.
Wren Engine is a semantic engine designed for MCP (Model Context Protocol) clients and AI agents, including Wren AI's GenBI AI Agent. It addresses the challenge of enterprises needing accurate semantic understanding of their data models for AI to effectively interact with structured data in cloud warehouses and databases.
Wren Engine's mission is to power the future of MCP clients and AI agents by providing a semantic layer that enables AI agents to access business data with accuracy, context, and governance. It is designed to be embeddable, interoperable with data stacks like PostgreSQL and Snowflake, semantic-first, and governance-ready, respecting roles and access controls.
Key concepts include MDL (Modeling Definition Language) and the benefits of using Wren Engine with LLMs. The project is currently in beta, with bi-weekly releases planned. The community is encouraged to provide feedback via Discord or GitHub Issues.