Developing a local OpenTelemetry viewer for developers and AI agents alike

说明与用途

开发者可以使用 otel‑gui 快速检查应用程序发送的遥测数据，该工具支持跟踪、日志和指标，并为 AI 代理提供 MCP API。

问题

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.

结果

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.

工作流

• 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.

证据

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.

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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.

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

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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.

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