Hive
NormalDescription
Hive is a production-ready multi-agent execution harness providing state management, failure recovery, observability, and human-in-the-loop control with auto-generated multi-agent topologies for complex business workflows.
Key Features
- Zero-setup, model-agnostic execution harness that auto-generates multi-agent topologies for complex workflows
- Graph-based execution DAG for safe parallel task coordination with deterministic fault tolerance
- Persistent role-based memory that evolves with project context — no manual state management
- Built-in human-in-the-loop (HITL) control, observability, and cost enforcement
- Self-healing and adaptive agents that improve over time via failure capture and graph evolution
- 102 MCP tools integrated, supporting OpenAI, Anthropic, Google Gemini and other major models
Use Cases
💡 Move AI agents from prototype to production for long-running complex business workflows
💡 Automated tasks requiring state persistence and crash recovery, like data processing pipelines
💡 Multi-agent collaboration with session isolation and shared buffers for parallel execution
💡 Enterprise AI agent deployment requiring cost auditing, observability, and compliance
💡 Build adaptive agent systems that scale automatically with model capability improvements
Categories
Quick Start
Clone the repo and run ./quickstart.sh (macOS/Linux) or .\quickstart.ps1 (Windows) to auto-configure framework, tools, credential store, and LLM provider. Once installed, the Hive dashboard opens in your browser — describe your agent in the input box and the Queen guides you through setup. Run hive open to reopen the dashboard anytime.