As companies integrate AI into their workflows, connecting new tools to their existing data while ensuring consistent security and accuracy becomes increasingly important. We’re introducing Looker Model Context Protocol (MCP) Server, an integration in the MCP Toolbox for Databases. This allows AI applications such as chatbots and custom agents to connect to trusted data from the environments AI developers use every day.
Looker already helps thousands of organizations to access, analyze, and act on a single, consistent, and governed view of their data through its robust semantic layer, connecting to hundreds of data sources such as BigQuery, AlloyDB, and Cloud SQL. With the launch of the Looker in MCP Toolbox, we are extending our leadership in trusted generative AI for BI by bringing this functionality to the emerging world of AI applications and agents.
MCP is an open standard technology that allows large language models (LLMs) and AI applications to access other products consistently and securely. Looker’s MCP Toolbox integration connects applications to the LLM along with structured metadata and specific request parameters. In addition, the MCP Server can expose unstructured natural language information about how the data source is called and what type of information it returns.
MCP essentially acts as a universal translator, enabling AI models to:
- Discover and use tools dynamically: Rather than hardcoded integrations, AI agents can identify and interact with available capabilities in real-time.
- Access relevant, up-to-date context: AI models can pull live, verified information directly from its source, significantly reducing hallucinations and improving response accuracy.
- Ensure secure and governed data access: MCP provides a host-mediated security model, allowing fine-grained control over what data AI agents can access and how.
Source Credit: https://cloud.google.com/blog/products/business-intelligence/introducing-looker-mcp-server/
