kafka-sentinel-mcp
Related Servers
Alternatives to kafka-sentinel-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityBmaintenanceMCP server that exposes Kafka debugging to an LLM: find messages, measure lag, unblock consumers. Read-only endpoints, previews before writes.251MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that gives AI agents real-time observability into Apache Kafka clusters, enabling natural language queries for broker health, consumer lag, and diagnostics.MIT
- AlicenseNot gradedqualityBmaintenanceThis read-only MCP server lets AI assistants inspect Apache NiFi, ClickHouse, and Kafka across multiple environments through natural language. It provides health checks, flow and message searches, querying and metadata tools while enforcing OIDC or proxy authentication, per-user auditing, secret masking, and two-lock read-only safeguards.Apache 2.0
- AlicenseBqualityBmaintenanceMCP server for Apache Kafka that allows LLM agents to inspect topics, consumer groups, and safely manage offsets (reset, rewind).1913Apache 2.0
- FlicenseAqualityDmaintenanceRead-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.6-

Conduktor MCP Serverofficial
AlicenseNot gradedqualityBmaintenanceEnables Claude, Cursor, or any MCP-compatible client to query Apache Kafka topics, consumer groups, schemas, and cluster health in natural language, served from your own self-hosted instance. Access is read-only and inherits the token holder's existing RBAC, so only metadata reaches the model unless a capped message-reading tool is explicitly used.44 npm5Apache 2.0
TDQS
Scored across 8 tools
Most tools target clearly distinct concerns: health, lag, audit, partition state, replay readiness. However, cluster_health and incident_snapshot overlap in scope since the snapshot bundles the health data, and topic_audit vs partition_state both touch replication/durability concerns at the partition level, creating minor confusion.
Tool names use a consistent noun-based pattern (adjective_noun) like cluster_health, consumer_lag, topic_audit, partition_state — not strictly verb_noun but internally consistent. Minor deviation is having two 'list_' verbs mixed in with the descriptive noun pattern, though this reads as intentional since they are discovery operations.
Eight tools for a Kafka operational monitoring server is a reasonable, focused scope. Each tool maps to a distinct operational concern with no obvious redundancy, and the incident_snapshot aggregation is a valuable convenience rather than bloat.
The surface covers the core read-only operational concerns an agent would need: discovery (list_topics, list_consumer_groups), health, lag, audit, partition state, and replay/retention analysis. Minor gaps exist — there's no consumer group reset or topic config mutation (read-only by design), and no offset trimming tool, but for an operational sentinel these are reasonable absences.