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Orchestrate local Hotwired multi-agent workflows with messaging, protocol, and task management.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "hotwired-mcp" yet — see the docs or source repo.
Using hotwired-mcp, design a local multi-agent workflow with a coordinator agent, coding agent, and testing agent communicating via Unix sockets. Define task routing, state synchronization, and retry handling.
A multi-agent workflow plan describing agent roles, communication, task flow, and fault tolerance.
With hotwired-mcp, create an inter-agent messaging protocol including message types, field schemas, task status update formats, and examples for error handling and acknowledgements.
A structured messaging protocol specification ready for local agent communication implementation.
Use hotwired-mcp to plan a task management setup where multiple AI agents handle subtasks in parallel, including task queues, priorities, progress tracking, and result aggregation.
A task orchestration and monitoring design for managing and observing multi-agent execution.
Connect to the mcp API via MCP to extend AI tool capabilities.
Connect once to access tools aggregated from many upstream MCP servers.
Call tools like weather lookup via MCP with reusable resources and prompts.
Build extensible, hot-reloadable, secure MCP tool servers quickly.
Build MCP servers and custom agent tools faster with a development framework.
Connect multiple MCP servers through one gateway for unified tool access.