frontmcp-observability

name	frontmcp-observability
description	Use when adding tracing, structured logging, metrics, or monitoring to a FrontMCP server. Covers zero-config OpenTelemetry distributed tracing across all flows; the this.telemetry API for custom spans, events, and attributes in tools, plugins, agents, and skills; structured JSON logging with trace correlation and configurable sinks (Winston, Pino, stdout); the off-by-default /metrics endpoint (process and framework metrics, Prometheus-compatible); vendor integrations (Coralogix, Datadog, Logz.io, Grafana Cloud, or any OTLP backend); and testing spans, log correlation, and instrumentation. Triggers: observability, telemetry, tracing, logging, monitoring, OpenTelemetry, OTel, spans, metrics, Prometheus, Datadog, Coralogix, Logz.io, Grafana, Winston, Pino.
tags	["router","observability","telemetry","tracing","logging","monitoring","opentelemetry","otel","spans"]
category	observability
targets	["all"]
bundle	["recommended","full"]
priority	10
visibility	both
license	Apache-2.0
metadata	{"docs":"https://docs.agentfront.dev/frontmcp/guides/observability"}

FrontMCP Observability

Router for adding observability to FrontMCP servers. Covers distributed tracing (OpenTelemetry), structured JSON logging, per-request log collection, the this.telemetry developer API, and vendor integrations.

When to Use This Skill

Must Use

• Adding tracing, logging, or monitoring to a FrontMCP server
• Connecting Coralogix, Datadog, Logz.io, Grafana, or any OTLP backend
• Using this.telemetry to create custom spans in tools, plugins, or agents
• Setting up structured logging with winston, pino, or NDJSON stdout
• Testing that spans and log entries are created correctly

Recommended

• Before going to production (see also frontmcp-production-readiness)
• When debugging request latency or error rates
• When building plugins that need trace context propagation

Skip When

• Building a prototype that doesn't need observability yet
• Configuring auth, transport, or throttle (see frontmcp-config)
• Setting up the project from scratch (see frontmcp-setup)

Decision: Use this skill when you need to observe, trace, or log your server. Start with tracing-setup for auto-instrumentation, add structured-logging for production logs, and use telemetry-api for custom spans in your code.

Prerequisites

• A working FrontMCP server (see frontmcp-setup)
• npm install @frontmcp/observability

Step 1: Choose What You Need

I want to...	Reference
Enable auto-tracing for all flows	references/tracing-setup.md
Add structured JSON logging with trace correlation	references/structured-logging.md
Create custom spans in tools/plugins	references/telemetry-api.md
Connect Coralogix, Datadog, Logz.io, Grafana	references/vendor-integrations.md
Test that spans and logs are correct	references/testing-observability.md