{
  "id": 16532197,
  "title": "Developing a local OpenTelemetry viewer for developers and AI agents alike",
  "url": "https://urgent.news/2026/10/25/developing-a-local-opentelemetry-viewer-for-developers-and-ai-agents",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-25T23:26:24.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/metafab/developing-a-local-opentelemetry-viewer-for-developers-and-ai-agents-alike-243f"
  },
  "original_language": "en",
  "account": "A local OpenTelemetry viewer, named otel-gui, is being developed to assist developers and AI agents in quickly understanding the telemetry generated by their applications. OpenTelemetry allows for the collection of traces, logs, and metrics from an application without requiring a specific observability vendor. However, when debugging locally, it is still necessary to know how to view the generated telemetry. The otel-gui tool aims to simplify this process by providing a local viewer that can be pointed at an OpenTelemetry exporter, allowing developers to explore the telemetry without setting up a full observability stack. The tool listens on port 4318, the standard OTLP/HTTP port, so many applications can send telemetry to it with minimal configuration. It supports both OTLP JSON and Protobuf formats and does not require a database to get started. Initially focusing on traces, otel-gui provides a trace viewer that groups spans in a waterfall view, making it easy to see the flow of a request and identify errors. The tool also offers a service map to visualize cross-service calls and their bottlenecks. Later versions added correlated logs and metrics to enrich the telemetry visualization. One of the key design choices in otel-gui is to keep the default setup small, retaining telemetry in memory by default, which allows for quick exploration without the need for a database. Optional persistence is available for more advanced setups. Another important feature is the ability to export and import telemetry data, enabling sharing of traces and logs with others for collaboration and debugging purposes. This export/import functionality complements the local-first approach by allowing controlled sharing of telemetry while keeping the primary data local and disposable. The upcoming version 3.1 will include an MCP server and HTTP endpoints, providing a read-only interface for AI agents to search for traces, logs, and metrics, fetch individual records, list services, and view the service map. This direct access to telemetry data will make it easier for AI agents to ask questions and retrieve relevant records, rather than relying on a browser UI or interpreting screenshots. By providing a visual interface that highlights the timing, hierarchy, and details of telemetry, otel-gui helps developers and AI agents form and test hypotheses, making debugging a more efficient process.",
  "summary": "Developing a local OpenTelemetry viewer for developers and AI agents alike OpenTelemetry makes it possible to collect traces, logs, and metrics from an application without tying your instrumentation to a particular observability vendor. But when you are developing locally and something goes wrong, there is still a practical question: How do you quickly see what your application just sent? During…",
  "key_points": [
    "otel-gui is a local OpenTelemetry viewer for developers and AI agents.",
    "The tool simplifies telemetry exploration with a trace viewer and service map.",
    "Upcoming version 3.1 adds MCP server for AI agent telemetry search."
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}