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Related Servers

Alternatives to agent-orchestrator

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding providers to run structured multi-agent workflows with tracked tasks, specifications, handoffs, and health-gated completion. It exposes MCP tools for task claiming, action logging, repairs, document validation, and lifecycle evidence.
      29 npm
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding providers to run structured multi-agent workflows with document-backed specifications, tracked tasks, handoffs, health gates, and completion evidence. It exposes MCP tools for coordinating use cases, specs, implementation, review, and repair across supported providers.
      29 npm
      MIT
    • F
      license
      C
      quality
      B
      maintenance
      Enables AI agents to collaborate via shared blackboard state, multi-agent deliberation, human-in-the-loop proposal approval, operating-mode control, and audit logging through MCP.
      11
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      MCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.
      60
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables users to delegate text and code tasks across multiple AI models with automatic failover, maintain shared mission memory and checkpoints across MCP harnesses, and coordinate parallel role-based subagents. It also supports model discovery, provider inventory, health checks, and stdio/HTTP tool access while leaving patches and tests to the harness.
      24
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables MCP hosts to run auditable multi-agent work through a SQLite task registry, DAG orchestration, three collaboration modes (pipeline, iterative refinement, and proposal voting), human-in-the-loop approvals, an enforced sandbox, compliance scanning, and long-term memory. Exposes these capabilities as 36 tools so every consequential step stays gated behind a human checkpoint.
      AGPL 3.0