The Kafka MCP Server provides an efficient way to turn prompts into actions within the Kafka ecosystem. It is a natural language interface designed for agentic applications to streamline Kafka operations and integrate seamlessly with MCP Clients, enabling AI-driven workflows to interact with Kafka processes. Typical use cases include publishing a message to a topic, consuming messages, and listing topics within a Kafka environment. The server exposes a set of tools for common Kafka operations: consumer and producer tools to publish and consume messages on topics; topic tools to list, create, delete, and describe topics; broker tool to retrieve broker information; partition tool to fetch partitions and partition offsets; and group_offset tool to get and reset consumer offsets. For development and deployment, configure BOOTSTRAP_SERVERS and MCP_TRANSPORT in a .env file, or via environment variables, and start the application with python3 src/main.py. It can be integrated with MCP clients through a config.json file, supporting multiple MCP servers. The design emphasizes scalability and lightweight operation for high‑performance data tasks.