MCP Standards

# Automatic Topology Selection ## Purpose Automatically select the optimal swarm topology based on task complexity analysis. ## How It Works ### 1. Task Analysis The system analyzes your task description to determine: - Complexity level (simple/medium/complex) - Required agent types - Estimated duration - Resource requirements ### 2. Topology Selection Based on analysis, it selects: - **Star**: For simple, centralized tasks - **Mesh**: For medium complexity with flexibility needs - **Hierarchical**: For complex tasks requiring structure - **Ring**: For sequential processing workflows ### 3. Example Usage **Simple Task:** ``` Tool: mcp__claude-flow__task_orchestrate Parameters: {"task": "Fix typo in README.md"} Result: Automatically uses star topology with single agent ``` **Complex Task:** ``` Tool: mcp__claude-flow__task_orchestrate Parameters: {"task": "Refactor authentication system with JWT, add tests, update documentation"} Result: Automatically uses hierarchical topology with architect, coder, and tester agents ``` ## Benefits - 🎯 Optimal performance for each task type - 🤖 Automatic agent assignment - ⚡ Reduced setup time - 📊 Better resource utilization ## Hook Configuration The pre-task hook automatically handles topology selection: ```json { "command": "npx claude-flow hook pre-task --optimize-topology" } ``` ## Direct Optimization ``` Tool: mcp__claude-flow__topology_optimize Parameters: {"swarmId": "current"} ``` ## CLI Usage ```bash # Auto-optimize topology via CLI npx claude-flow optimize topology ```