Developing a local OpenTelemetry viewer for developers and AI agents alike

Description and use

Developers can quickly inspect telemetry sent by their application using otel‑gui, a local OpenTelemetry viewer that supports traces, logs, and metrics, and offers an MCP API for AI agents.

Problem

During local development, developers need a quick way to inspect the telemetry (traces, logs, metrics) their application sends without setting up a full observability stack.

Outcome

Developers can validate telemetry locally with minimal setup, while AI agents can query the same data via MCP or HTTP APIs, enabling faster debugging and collaboration.

Workflow

• 1. Run otel‑gui locally (listens on port 4318).
• 2. Configure application to export OTLP to localhost:4318.
• 3. Trigger a request or reproduce a problem.
• 4. Open the otel‑gui UI to view traces, logs, metrics, service map.
• 5. Use export/import to share telemetry files.
• 6. For AI agents, connect via MCP endpoint or HTTP API to query telemetry programmatically.

Evidence

I started building otel-gui to make that step easier: point an OpenTelemetry exporter at a local viewer, execute a request or reproduce a problem, and explore the telemetry without first setting up a full observability stack.

Source

It listens by default on port 4318, the standard OTLP/HTTP port, so many applications can send telemetry to it with little or no exporter reconfiguration.

Source

otel-gui also supports exporting and importing telemetry data, making it easier to share traces and logs with others.

Source

otel-gui provides a read-only Model Context Protocol (MCP) endpoint with tools for searching traces, logs, and metrics; fetching individual records; listing services; and viewing the service map.

Source