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Coordinate multi-device LLM agent teams with shared memory, tasks, and live status.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ATMcp" yet — see the docs or source repo.
Design an ATMcp-based multi-agent workflow for my project with three roles: coding, testing, and documentation. Explain task division, shared memory, task-status syncing, and provide implementation steps.
A clear multi-agent collaboration architecture with role assignments, communication flow, and implementation steps.
I want to use ATMcp to manage multiple AI agents across different devices. Help me plan a visual monitoring setup showing task status, retry handling, knowledge sharing, and alerting.
A dashboard plan for operations and collaboration management, highlighting live status and reliability design.
Using ATMcp, design a workflow for multiple LLM agents to share context, long-term memory, and intermediate results for ongoing research tasks, and explain how to avoid information conflicts.
A knowledge-sharing workflow for continuous collaborative research, including memory management and conflict-control guidance.
Orchestrate multiple AI agents in real time and monitor tasks and artifacts.
Coordinate specialized AI agents for software development, review, testing, and task tracking.
Enable AI agents to communicate, route messages, and collaborate through MCP.
Connect multiple AI agents to one chatroom for collaborative conversations.
Create, manage, and compose AI agents for MCP-compatible clients and tools.
Coordinate multiple AI agents on software projects with shared tasks and context.