Kafka Schema Registry MCP Server

The Kafka Schema Registry MCP Server is a dedicated Model Context Protocol (MCP) implementation that bridges AI assistants such as Claude Desktop with Confluent’s Kafka Schema Registry. By exposing the registry’s RESTful API through MCP, developers can ask natural‑language questions about schemas, register new ones, and manage multiple registry instances—all without leaving their conversational workflow. This eliminates the need for manual API calls or separate tooling, allowing data engineers and SREs to focus on business logic while the assistant handles routine schema operations.

At its core, the server translates MCP messages into standard Schema Registry requests. It can list available subjects, fetch schema definitions by version or ID, register new schemas with validation, and delete obsolete ones. The integration is fully compliant with the MCP 2025‑06‑18 specification, ensuring seamless communication over JSON‑RPC via . The FastMCP framework powers the server, providing robust performance and low overhead even when handling dozens of concurrent schema requests.

Key capabilities include:

• Multi‑registry management: Configure up to eight distinct Schema Registry endpoints, each with its own authentication and configuration. This is ideal for environments that separate development, staging, and production clusters or that use multiple Kafka deployments.
• Schema context support: Group schemas into logical contexts, enabling the assistant to filter and display only relevant subjects for a given project or team.
• Export and import tooling: Export all schemas from a registry to a local archive or import them into another instance, simplifying migrations and disaster‑recovery procedures.
• SLIM_MODE operation: Run the server with a reduced toolset to lower memory usage and attack surface, suitable for production deployments where only core schema operations are required.

In practice, a data engineer might ask Claude, “Show me all user‑related schemas in the production context,” and receive a structured list of subjects with their latest versions. An SRE could request, “Register a new user schema with fields for id, name, and email,” and the assistant would automatically construct the Avro definition, validate it against existing subjects, and push it to the registry. For migration projects, an engineer could prompt, “Export schemas from staging and import them into production,” and the MCP server would handle all the necessary API calls, ensuring consistency across environments.

By embedding schema management into an AI‑driven conversational interface, the Kafka Schema Registry MCP Server streamlines routine tasks, reduces context switching, and lowers the barrier to entry for teams that rely on Kafka. Its compliance with MCP standards guarantees compatibility across future AI assistants, while the lightweight Docker image and optional SLIM_MODE make it easy to deploy in CI/CD pipelines or on edge devices. This combination of developer‑friendly APIs, robust multi‑registry support, and natural‑language orchestration positions the server as a valuable asset for any organization seeking to modernize its Kafka infrastructure.