openclaw-dashboard and openclaw-command-center

These tools are competitors, as both aim to provide a command center dashboard for OpenClaw AI agents, implying a user would choose one over the other for the same core functionality.

openclaw-dashboard
56
Established
openclaw-command-center
54
Established
Maintenance 13/25
Adoption 10/25
Maturity 11/25
Community 22/25
Maintenance 13/25
Adoption 10/25
Maturity 11/25
Community 20/25
Stars: 261
Forks: 51
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 136
Forks: 26
Downloads:
Commits (30d): 0
Language: JavaScript
License: MIT
No Package No Dependents
No Package No Dependents

About openclaw-dashboard

mudrii/openclaw-dashboard

A beautiful, zero-dependency command center for OpenClaw AI agents

Provides real-time operational visibility into OpenClaw AI agent deployments through 12 dashboard panels covering gateway health, cost breakdown (daily/monthly projections), cron job status, active sessions with token usage, and sub-agent activity — all refreshed automatically every 60 seconds. Built as a single Go binary backend with pure HTML/CSS/JS frontend, it polls OpenClaw's `/healthz`, `/readyz`, and `status --json` endpoints locally over HTTP, featuring 6 themeable interfaces, rate-limited natural-language chat queries, and per-metric CPU/RAM/disk thresholds. Designed specifically for multi-agent, multi-model OpenClaw setups running dozens of cron jobs across Telegram, Slack, Discord, and WhatsApp integrations.

About openclaw-command-center

jontsai/openclaw-command-center

🤖 AI assistant command and control dashboard — Spawn more Overlords!

Provides real-time monitoring and cost analysis for OpenClaw AI agents with a lightweight, zero-dependency UI built on vanilla JavaScript and Server-Sent Events (SSE) streaming. Supports multiple authentication modes (token, Tailscale, Cloudflare, IP allowlist) and auto-detects OpenClaw workspaces without configuration. Integrates with OpenClaw's session management, Slack threading, and Cerebro topic tracking to deliver unified visibility into active sessions, LLM token usage, system vitals, scheduled tasks, and per-model cost breakdowns.

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