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Coordinate multiple AI agents with shared context, task orchestration, and live collaboration.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "subhive" yet — see the docs or source repo.
Use subhive to create a task DAG for a project with research, coding, and testing AI agents, define dependencies, and suggest automatic scheduling.
A collaboration plan with agent roles, task dependencies, and scheduling order.
Explain how to configure shared semantic memory in subhive so multiple AI agents can continue working from the same context.
Guidance on organizing shared context and enabling multi-agent collaboration.
Based on subhive's role-based access, real-time push, and live dashboard, design a multi-agent collaboration setup for a team.
A collaboration design covering permission levels, live notifications, and monitoring views.
Developers or DevOps teams can use it to manage shared context and task dependencies across multiple AI agents, reducing handoff friction and repeated coordination. It fits complex workflows that need auto-scheduling and continuous collaboration.
When multiple agents need different responsibilities, role-based access can control collaboration scope while real-time push keeps everyone synchronized. The live dashboard helps teams monitor overall progress.
In workflows with prerequisite relationships, it can organize work as a DAG and automatically schedule execution order. This is useful for multi-agent processes that require clear stage transitions.
It is an MCP-based shared context and coordination layer for multiple AI agents. The description says it includes semantic memory, task DAGs, auto-scheduling, role-based access, real-time push, and a dashboard.
Based on the description, it is primarily designed for collaboration and coordination across multiple AI agents. Its core value is shared context and cross-agent task orchestration.
The provided material does not include installation steps, runtime details, or key requirements. See the source repository for specifics.
Enable collaborative AI agents with shared mailboxes, identity, and notifications.
Self-host shared memory, RAG search, and persistent context for AI agents.
Coordinate multi-agent AI workflows across clients with delegation and shared artifacts.
Shared project wiki for AI agents to manage pages, actions, and logs.
Shared memory and workflow state for multi-agent collaboration.
Coordinate AI agent teams with shared memory, kanban workflows, and live oversight.