Read-only Kafka visibility through Conduktor Console, covering clusters, topics, messages, consumer groups, schemas, access, lineage, and cost.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
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π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Conduktor.
list-clustersEvery Kafka cluster this Console manages, with its Schema Registry, Connect clusters and flavor
get-clusterOne cluster's registration by slug
insights-clusterHealth score, topic and partition counts, serialization breakdown β the shape of a cluster in one call
list-topicsTopic catalogue: names, labels, descriptions, partitions, replication, configs
get-topicOne topic by exact name
list-topics-with-usageTopics with message count, size and throughput
The Conduktor MCP server gives AI assistants an MCP interface to Kafka estates registered in Conduktor Console. It covers both Kafka resource inspection and related Console control-plane metadata, including cluster registrations, topic catalogues, consumer groups, schemas, certificates, applications, permissions, lineage, audit activity, and team chargeback information.
The supplied tools are primarily read-oriented. They can show cluster health, topic usage, partition and replication issues, consumer lag, recent records, records at specific offsets, schema versions, and compatibility results. This makes the server suitable for investigation and operational questions where the assistant needs current information from Console rather than static documentation.
The server endpoint runs inside Conduktor Console. A client launches the published @conduktor/mcp package, which connects to the Console MCP endpoint; the package appends /api/mcp to the configured Console URL when needed. The repository also documents a direct mcp-remote setup for clients that do not use the package wrapper.
Each request carries a Console Personal Access Token. Console RBAC determines which clusters and resources the caller can access, and calls are recorded in the Console audit log. The material describes the model-facing data as control-plane metadata, while Kafka records remain in Kafka unless a task uses a tool that reads them. Message inspection tools such as get-last-messages and get-record-at are exceptions that can retrieve record data.
Create a Personal Access Token in Conduktor Console, then configure an MCP client with the launcher:
CONDUKTOR_CONSOLE_URL identifies the Console instance, and CONDUKTOR_API_TOKEN supplies authentication. URLs that already end with /api/mcp are accepted. As an alternative, invoke mcp-remote directly and pass the token as a Bearer authorization header.
The repository includes a demo environment that starts Kafka, Console, and the MCP endpoint with Docker Compose. It is seeded with topics, traffic, and a lagging consumer group for evaluation without an existing Kafka estate.
The Conduktor MCP server exposes tools in these areas:
The server depends on Conduktor Console and an authorized Personal Access Token; it is not a standalone Kafka deployment or a replacement for Console. Access is limited by the token holder's Console RBAC permissions, so an assistant cannot see resources unavailable to that identity.
The supplied listing describes the current use case as read-only Kafka access. Although the repository documentation discusses a broader agent model and additional operational workflows, the tools listed for this entry should be treated as the supported interface when evaluating coverage.
The endpoint runs inside Console, so there is no separate server deployment described for production use. For launcher or repository issues, the README distinguishes those from issues with the server running in Console, which should go through Conduktor support.
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