MCP + Metrics

The MCP + Metrics overlay combines the core stack with both Prometheus monitoring and the StreamsHub MCP server. The MCP server is configured to use Prometheus as its centralized metrics provider.

Quick-Start Install #

curl -sL https://raw.githubusercontent.com/streamshub/developer-quickstart/main/install.sh | OVERLAY=mcp-metrics bash

Manual Install #

If you prefer step-by-step control, the MCP + Metrics overlay uses overlays/mcp-metrics:

# Phase 1 — Operators and CRDs (includes Prometheus Operator)
kubectl apply --server-side --force-conflicts -k 'https://github.com/streamshub/developer-quickstart//overlays/mcp-metrics/base?ref=main'

# Optionally, wait for the operators to be ready
kubectl wait --for=condition=Available deployment/prometheus-operator -n monitoring --timeout=120s
kubectl wait --for=condition=Available deployment/strimzi-cluster-operator -n strimzi --timeout=120s
kubectl wait --for=condition=Available deployment/apicurio-registry-operator -n apicurio-registry --timeout=120s
kubectl wait --for=condition=Available deployment/streamshub-console-operator -n streamshub-console --timeout=120s

# Phase 2 — Operands, MCP server, Prometheus instance and monitors
kubectl apply -k 'https://github.com/streamshub/developer-quickstart//overlays/mcp-metrics/stack?ref=main'

Uninstall #

curl -sL https://raw.githubusercontent.com/streamshub/developer-quickstart/main/uninstall.sh | OVERLAY=mcp-metrics bash

What Gets Added #

On top of the components provided by the core overlay, the MCP + Metrics overlay adds:

Component	Namespace	Description
Prometheus Operator	`monitoring`	Manages Prometheus instances and monitors
Prometheus instance	`monitoring`	Collects and stores metrics (400Mi memory, 1 replica)
PodMonitors	`monitoring`	Scrape targets for Kafka brokers and Strimzi operators
ServiceMonitor	`monitoring`	Scrape target for StreamsHub Console operator
StreamsHub MCP server	`streamshub-mcp`	MCP server configured with Prometheus metrics provider
MCP PodMonitor	`monitoring`	Scrape target for MCP server metrics
Sensitive Role	`kafka`	Grants access to TLS certificates and pod metrics

The overlay patches existing resources:

Kafka — enables the Strimzi Metrics Reporter on the dev-cluster
Console — adds Prometheus as a metrics data source so the Console UI displays Kafka metrics
MCP server — configured to use Prometheus as centralized metrics provider instead of direct pod scraping

Resource Requirements #

The MCP + Metrics overlay requires at least 3 CPU cores and 5.5 GiB of allocatable cluster resources. This includes the resources for the core stack plus the additional components listed above.

Accessing the MCP Server #

Port-forward to the MCP server:

kubectl port-forward -n streamshub-mcp svc/streamshub-strimzi-mcp 8085:8080

The MCP endpoint is available at http://localhost:8085/mcp.

Accessing Prometheus #

Port-forward to the Prometheus UI:

kubectl port-forward -n monitoring svc/prometheus-operated 9090:9090

Open http://localhost:9090 and navigate to Status > Targets to verify all scrape targets are up, including the MCP server.

Verify the Installation #

Confirm all components are running:

kubectl get deployment -n streamshub-mcp streamshub-strimzi-mcp
kubectl get prometheus -n monitoring
kubectl get podmonitor -n monitoring

The MCP server deployment should show 1/1 ready replicas. Prometheus should reach Available status.

StreamsHub

Overlays