ai-maestro
Reduces AI agent fragmentation and operational overhead by centralizing multi-agent orchestration, enabling teams to manage distributed agents across infrast…
AI Agent Orchestrator with Skills System - Give AI Agents superpowers: memory search, code graph queries, agent-to-agent messaging. Manage Claude, Codex or any AI Agent from one dashboard. Move Agents between computers and locations
- Ask Claude to search memory across multiple agents to find previous solutions to similar problems.
- Generate code graph queries to understand dependencies between services before refactoring architecture.
- Automate deployment of AI agents across different environments from a single dashboard control.
Reduces AI agent fragmentation and operational overhead by centralizing multi-agent orchestration, enabling teams to manage distributed agents across infrastructure without rebuilding integration logic.
Engineering teams deploying multiple AI agents across distributed systems or cloud environments needing unified control and inter-agent coordination.
https://github.com/23blocks-OS/ai-maestro
By 23blocks-OS
How to Get It
claude plugins install 23blocks-OS/ai-maestro
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Search memory across multiple agents to find previous solutions to similar problems
Trust Signals Auto-scanned
Community Pulse New
- AI Maestro Agent Orchestration — Hacker News · 3 pts
- AI-maestro: Conduct a roster of AI coding agents against a work board — Hacker News · 2 pts
2 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 735 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 735 GitHub stars; contributors unknown; last commit 0d ago; license MIT.