MCP is a protocol for connecting third-party services to Large Language Models (LLMs). Creating an MCP server defines how a client can interact with the service. An MCP client connects to the server, allowing the LLM to interact with the service. MCP is becoming the de-facto protocol and has been implemented in ClickHouse, a database designed for interactive analytics at scale. Natural language interfaces are becoming popular across various domains, including data analysis, making it easier than ever to work with data. The expectation of speed and interactivity in user experience is universally expected, and LLMs are helping to round out people's skills. ClickHouse is the ideal database for agentic AI data workflows due to its fast analytical capabilities and support for interactive analytics at scale. Various frameworks such as Agno, DSPy, LangChain, LlamaIndex, and PydanticAI have been implemented to integrate with MCP, allowing developers to build applications that expose data to end-users and generate insights without SQL. The examples provided demonstrate how to initialize the MCP server and create agents using these frameworks, showcasing the potential of MCP in building production-grade applications with Generative AI.