Efficiency Improvement Program
To optimize the efficiency of multi-agent communication, the core is the rational application of MCP protocol and Planner function:
- Enable MCP protocol: Set in .env
MCP_AGENT=TrueThe protocol standardizes the format of information exchange between agents and supports context management for multi-round conversations. - Task decomposition strategy: In Agent Workflow mode, the system Planner automatically splits complex tasks into atomic subtasks and assigns them to the most appropriate agents
- Communication Optimization Practice::
- Define clear scopes of responsibility for each agent (see Excel agent sample code)
- utilization
MCPManager.register_agent()Registering proxies for high-frequency calls - Configure a reasonable session timeout in the server parameters
Performance Monitoring Essentials::
- pass (a bill or inspection etc)
cli.py statusChecking the status of agent operation - Examine the interaction logs in the logs directory, focusing on analyzing task wait time consumption
- Consider merging groups of agents that communicate frequently into composite agents
This answer comes from the articleCooragent: building a multi-intelligence task collaboration tool in one sentenceThe
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