Useful MCP Resources for a Kafka‑MCP‑Server

Below is a curated list of “resources” your Kafka‑MCP‑Server should expose via the resources/list and resources/read endpoints. These resources let clients discover and pull Kafka‑related data—logs, configs, metrics, and schemas—using standardized URIs.

1. Direct Resources

Concrete, always‑available items:

• Kafka Broker Logs • URI: file:///var/log/kafka/server.log • Name: “Kafka Server Log” • Description: “Rolling broker activity log” • MIME Type: text/plain

• Broker Configuration • URI: kafka-mcp://cluster/config/broker.yaml • Name: “Broker Configuration” • Description: “YAML‑encoded Kafka broker settings” • MIME Type: application/x-yaml

• Topic Schemas • URI: kafka-mcp://cluster/schemas/all.json • Name: “All Topic Schemas” • Description: “JSON‑schema definitions for all topics” • MIME Type: application/json

• ACL Definitions • URI: kafka-mcp://cluster/security/acl.json • Name: “Access Control Lists” • Description: “Current ACL rules for cluster resources” • MIME Type: application/json

2. Resource Templates

Parameterized URIs for dynamic data:

• Topic Description • URI Template: kafka-mcp://{cluster}/topics/{topic}/describe • Name: “Describe Topic” • Description: “Partition, replica, and ISR details for a topic” • MIME Type: application/json

• Consumer Group Offsets • URI Template: kafka-mcp://{cluster}/consumerGroups/{groupId}/offsets • Name: “Consumer Group Offsets” • Description: “Current vs. end offsets per partition” • MIME Type: application/json

• Topic Messages • URI Template: kafka-mcp://{cluster}/topics/{topic}/messages?offset={offset}&count={n} • Name: “Fetch Topic Messages” • Description: “Retrieve a batch of messages from a topic” • MIME Type: application/json

• Cluster Metrics • URI Template: kafka-mcp://{cluster}/metrics/{metricType} • Name: “Cluster Metrics” • Description: “Time‑series data for CPU, memory, throughput, or latency” • MIME Type: application/json

3. Binary Resources

Non‑text data as base64‑encoded blobs:

• Dashboard Screenshot • URI Template: kafka-mcp://{cluster}/dashboards/broker/{brokerId}/screenshot.png • Name: “Broker Metrics Dashboard” • Description: “PNG snapshot of broker‑level metrics view” • MIME Type: image/png

• Partition Distribution Chart • URI Template: kafka-mcp://{cluster}/visualizations/{topic}/partition_distribution.svg • Name: “Partition Distribution” • Description: “SVG depicting partition leadership distribution” • MIME Type: image/svg+xml

4. Subscriptions & Updates

Support real‑time monitoring by notifying clients of resource changes:

• List Changes • Notification: notifications/resources/list_changed • Emitted when new topics, consumer groups, or schemata appear.

• Content Changes • Workflow:

  1. Client calls resources/subscribe with a resource URI (e.g., log file or metrics URI).

  2. Server emits notifications/resources/updated on changes.

  3. Client fetches updates via resources/read.

  4. Client calls resources/unsubscribe when done.

5. Best Practices

• Use clear, human‑readable name and description fields.

• Assign accurate mimeType for client parsing (e.g., application/json, image/png).

• Validate and sanitize template parameters (cluster, topic, groupId).

• Implement pagination or time‑range filtering for large logs and metrics.

• Cache frequently accessed resources, but signal stale data via updates.

6. Security Considerations

• Enforce access controls per URI (e.g., restrict config or ACL reads).

• Sanitize file paths to prevent directory traversal.

• Rate‑limit high‑volume reads (logs, metrics).

• Audit all resource accesses for traceability.

• Encrypt data in transit (TLS) and at rest if needed.

By exposing these MCP resources, your Kafka‑MCP‑Server empowers LLMs and client apps to discover and ingest Kafka operational data—logs, configs, schemas, metrics, and visuals—enabling rich, context‑aware AI interactions.