openclaw-mission-control and openclaw-command-center

These are ecosystem siblings—both are dashboard frontends that interface with the same OpenClaw Gateway backend for AI agent orchestration, with Mission Control offering broader multi-agent coordination while Command Center provides a lighter-weight assistant control interface.

Maintenance 25/25
Adoption 10/25
Maturity 11/25
Community 25/25
Maintenance 13/25
Adoption 10/25
Maturity 11/25
Community 20/25
Stars: 2,153
Forks: 480
Downloads:
Commits (30d): 109
Language: TypeScript
License: MIT
Stars: 136
Forks: 26
Downloads:
Commits (30d): 0
Language: JavaScript
License: MIT
No Package No Dependents
No Package No Dependents

About openclaw-mission-control

abhi1693/openclaw-mission-control

AI Agent Orchestration Dashboard - Manage AI agents, assign tasks, and coordinate multi-agent collaboration via OpenClaw Gateway.

Provides unified visibility and approval-driven governance for multi-team agent operations, with built-in activity audit trails and human-in-the-loop execution controls. Supports both Docker and local deployments with dual authentication modes (bearer token and Clerk JWT), exposing the same operational model through web UI and API-first interfaces. Gateway-aware architecture enables distributed runtime control across local and remote execution environments while maintaining a single system of record for organizations, boards, tasks, and approval workflows.

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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