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Wren Engine

> Wren Engine is the Semantic Engine for MCP Clients and AI Agents. > [Wren AI](https://github.com/Canner/WrenAI) GenBI AI Agent is based on Wren Engine.

## 🔌 Supported Data Sources - [BigQuery](https://docs.getwren.ai/oss/wren_engine_api#tag/BigQueryConnectionInfo) - [Google Cloud Storage](https://docs.getwren.ai/oss/wren_engine_api#tag/GcsFileConnectionInfo) - [Local Files](https://docs.getwren.ai/oss/wren_engine_api#tag/LocalFileConnectionInfo) - [MS SQL Server](https://docs.getwren.ai/oss/wren_engine_api#tag/MSSqlConnectionInfo) - [Minio](https://docs.getwren.ai/oss/wren_engine_api#tag/MinioFileConnectionInfo) - [MySQL Server](https://docs.getwren.ai/oss/wren_engine_api#tag/MySqlConnectionInfo) - [Oracle Server](https://docs.getwren.ai/oss/wren_engine_api#tag/OracleConnectionInfo) - [PostgreSQL Server](https://docs.getwren.ai/oss/wren_engine_api#tag/PostgresConnectionInfo) - [Amazon S3](https://docs.getwren.ai/oss/wren_engine_api#tag/S3FileConnectionInfo) - [Snowflake](https://docs.getwren.ai/oss/wren_engine_api#tag/SnowflakeConnectionInfo) - [Trino](https://docs.getwren.ai/oss/wren_engine_api#tag/TrinoConnectionInfo) ## 😫 Challenge Today At the enterprise level, the stakes - and the complexity - are much higher. Businesses run on structured data stored in cloud warehouses, relational databases, and secure filesystems. From BI dashboards to CRM updates and compliance workflows, AI must not only execute commands but also **understand and retrieve the right data, with precision and in context**. While many community and official MCP servers already support connections to major databases like PostgreSQL, MySQL, SQL Server, and more, there's a problem: **raw access to data isn't enough**. Enterprises need: - Accurate semantic understanding of their data models - Trusted calculations and aggregations in reporting - Clarity on business terms, like "active customer,"

#data-warehouse

Wren Engine

MCP Connector: Integrating AI agent with Data Warehouse in Microsoft Fabric