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Home/Categories/Security & Monitoring/ClawMetry
icon of ClawMetry

ClawMetry

Open source alternative to Arize AI and Datadog

  • 436 stars
  • MIT
  • Active this week
  • Last commit 3 days ago

Last verified Oct 20, 2026

Monitor AI-agent runtime activity with a local observability dashboard for costs, sessions, traces, crons, and approvals.

Visit websiteGitHub436 stars
image of ClawMetry
TL;DR

ClawMetry is an observability dashboard for OpenClaw AI agents. It replaces blind terminal watching with realtime visibility into agent activity, status, and traces for developers running OpenClaw locally or in experiments. MIT licensed.

Read the full breakdownHide the full breakdownWho it is for, how it works, trade-offs and the FAQ
who it's for

Who ClawMetry is for#

Developers debugging OpenClaw agents

ClawMetry helps developers see agent activity in realtime while testing prompts, tools, and long-running local tasks.

Skip if:

Your agent stack is not OpenClaw and you do not plan to add OpenClaw-specific instrumentation.

AI teams evaluating agent reliability

The dashboard can help small teams spot where agents stall, loop, or call tools unexpectedly during experiments.

Skip if:

You need enterprise observability with retention policies, alert routing, and compliance reporting.

the problem

The problem it solves#

Agent runs are hard to trust when developers cannot see what the agent is doing between prompts. Long-running tasks may stall, call tools unexpectedly, or fail silently while the operator only sees partial terminal output.

As agent workflows get more autonomous, teams need observability that explains behavior rather than only logging final results. Without that visibility, debugging agent failures becomes guesswork.

how ClawMetry solves it

How it solves it#

Realtime OpenClaw dashboard

ClawMetry focuses on showing OpenClaw activity as it happens, which helps operators understand agent state instead of waiting for a final response.

One-command setup

The README emphasizes one-command setup and automatic detection, which can reduce instrumentation work before observing an OpenClaw agent run.

OpenTelemetry-oriented monitoring

Repository topics include OpenTelemetry and observability, which fits teams that want agent monitoring to sit near existing telemetry habits.

strengths · trade-offs

Strengths and trade-offs#

Strengths

  • Built for a specific agent runtimeBecause ClawMetry targets OpenClaw, it can focus on the traces and events that matter for that agent workflow instead of being a generic log viewer.
  • Small-team friendly licenseMIT licensing makes it practical for developers to inspect, modify, and embed the observability workflow in internal agent experiments.

Trade-offs

  • -Narrow OpenClaw fitClawMetry is most useful if your agents run through OpenClaw. Teams using other agent frameworks may need adapters or a broader observability platform.
tech stack · detected from GitHub

What it's built on#

Languages
JavaScriptPythonTypeScript
Frameworks
React
frequently asked

FAQ#

What does ClawMetry monitor?

ClawMetry monitors OpenClaw AI agent activity. It is built to show what an OpenClaw agent is doing in realtime.

Is ClawMetry open source?

Yes. The GitHub repository reports MIT licensing.

Is ClawMetry useful without OpenClaw?

Its clearest fit is OpenClaw. Other agent runtimes may require different instrumentation or a general observability stack.

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