Add usage metrics for vMCP product telemetry

Summary

Implement product telemetry for vMCP to track usage patterns and inform product decisions.

Background

ToolHive has existing patterns for product telemetry:

• Operator telemetry in pkg/operator/telemetry/ for instance tracking
• Version checking and update notifications
• ConfigMap-based instance ID persistence

vMCP needs similar product telemetry to understand:

• How many vMCP instances are deployed
• What configurations are commonly used
• Tool call patterns and volumes

Reusable Patterns

Pattern	Location	Description
Instance Tracking	pkg/operator/telemetry/telemetry.go	Instance ID generation
Update Checking	pkg/updates/	Periodic telemetry collection

Implementation

Metrics to Track

Deployment Metrics:

• Number of vMCP instances
• Backends per vMCP (count distribution)
• Conflict resolution strategies used (prefix/priority/manual)
• Auth types configured (OIDC, anonymous, token exchange)

Usage Metrics:

• Tool calls per vMCP instance (aggregated)
• Composite tools defined and executed
• Backend distribution (which backends are most used)

Operational Metrics:

• vMCP uptime
• Configuration changes over time

Implementation Steps

1. Define telemetry data model

   • What data points to collect
   • Privacy considerations (no PII, no tool arguments)

2. Add collection mechanism

   • Periodic aggregation of usage data
   • Instance identification (anonymous ID)

3. Add reporting endpoint

   • Optional opt-in telemetry reporting
   • Clear documentation of what's collected

Privacy Considerations

• No personally identifiable information (PII)
• No tool arguments or resource content
• No authentication tokens or secrets
• Aggregated counts only (not individual requests)
• Clear opt-out mechanism

Acceptance Criteria

• Usage metrics defined and documented
• Collection mechanism implemented
• Privacy-preserving (no PII, aggregated data only)
• Opt-out mechanism available
• Documentation of what's collected
• Kubernetes and CLI deployment support

Start by reading the existing patterns in pkg/operator/telemetry/telemetry.go and pkg/updates/. Define the telemetry data model and privacy boundaries before designing collection and reporting for both Kubernetes and CLI deployments. Done means documented aggregated metrics, opt-out support, privacy safeguards, and implementation coverage for the listed acceptance criteria.