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ClawMetry for OpenClaw is a real-time observability dashboard for monitoring OpenClaw AI agents.
overview
ClawMetry for OpenClaw is a real-time observability dashboard tool developed by an independent creator that enables developers to monitor OpenClaw AI agents effectively. It provides detailed insights into multi-agent interactions, helping to debug complex workflows.
quick facts
| Attribute | Value | |-----------|-------| | Developer | Independent Creators | | Pricing | Freemium: Free | | Platforms | macOS, Linux, Windows, Raspberry Pi | | API Available | No | | Integrations | None specified | | Languages | Python 3.x |
features
ClawMetry provides several features designed to enhance observability for OpenClaw AI agents.
use cases
ClawMetry is particularly useful for developers and teams working with OpenClaw who require insights into their AI agent operations.
pricing
ClawMetry for OpenClaw is available as a completely free and open-source tool. There are no paid tiers or premium features.
competitors
ClawMetry for OpenClaw is positioned uniquely in the market for AI observability tools.
End-to-end platform that connects observability directly to systematic improvement with CI/CD-integrated evaluations.
While Braintrust offers broader AI observability beyond just OpenClaw agents, it provides more comprehensive evaluation and workflow features. Braintrust is framework-agnostic with stronger PM/engineer collaboration, whereas ClawMetry is purpose-built specifically for OpenClaw agents with real-time token cost monitoring.
Open-source LLM observability platform with tracing, prompt management, and evaluations supporting multi-turn conversations.
Langfuse is open-source with MIT licensing and broader LLM framework support, while ClawMetry is specifically optimized for OpenClaw agent monitoring. Both offer free tiers, but Langfuse targets teams using LangChain/LangGraph, whereas ClawMetry focuses on OpenClaw-specific metrics like sub-agent activity and session history.
AI Gateway with routing, failovers, rate limiting, and caching across 100+ models alongside evaluation capabilities.
Helicone combines gateway infrastructure with observability across multiple AI models, offering broader functionality than ClawMetry's agent-specific dashboard. ClawMetry provides more granular OpenClaw agent insights (cron jobs, memory changes), while Helicone emphasizes cost tracking and model routing across diverse LLM providers.
Enterprise-focused monitoring platform for both traditional ML and LLMs with emphasis on explainability, compliance, and security.
Fiddler targets enterprise deployments with regulatory compliance features, while ClawMetry is a lightweight, open-source dashboard for developers. ClawMetry offers simpler real-time visualization for OpenClaw agents, whereas Fiddler provides deeper explainability and drift detection for production ML systems.
Unified ML and LLM monitoring platform offering 100+ metrics, data drift detection, and open-source capabilities.
Evidently AI provides broader ML and LLM monitoring across multiple model types with extensive metrics, while ClawMetry specializes in real-time OpenClaw agent observability. Both offer free tiers, but ClawMetry's one-command installation and agent-specific features (token costs, sub-agent activity) make it more accessible for OpenClaw users compared to Evidently's broader ML focus.
ClawMetry for OpenClaw is a real-time observability dashboard tool developed by an independent creator that enables developers to monitor OpenClaw AI agents effectively. It provides detailed insights into multi-agent interactions, helping to debug complex workflows.
Yes, ClawMetry for OpenClaw is available as a completely free and open-source tool.
ClawMetry provides full chain tracing, real-time token cost monitoring, cron job visibility, session history tracking, and live flow visualization.
ClawMetry is ideal for developers, data scientists, operations teams, and AI researchers engaged with OpenClaw.
ClawMetry for OpenClaw is specifically tailored for OpenClaw agents and offers features such as granularity in observability, which differentiates it from more general multi-agent or enterprise-focused observability platforms.