MCP Server Trello

# swarm init Initialize a Claude Flow swarm with specified topology and configuration. ## Usage ```bash npx claude-flow swarm init [options] ``` ## Options - `--topology, -t <type>` - Swarm topology: mesh, hierarchical, ring, star (default: hierarchical) - `--max-agents, -m <number>` - Maximum number of agents (default: 8) - `--strategy, -s <type>` - Execution strategy: balanced, parallel, sequential (default: parallel) - `--auto-spawn` - Automatically spawn agents based on task complexity - `--memory` - Enable cross-session memory persistence - `--github` - Enable GitHub integration features ## Examples ### Basic initialization ```bash npx claude-flow swarm init ``` ### Mesh topology for research ```bash npx claude-flow swarm init --topology mesh --max-agents 5 --strategy balanced ``` ### Hierarchical for development ```bash npx claude-flow swarm init --topology hierarchical --max-agents 10 --strategy parallel --auto-spawn ``` ### GitHub-focused swarm ```bash npx claude-flow swarm init --topology star --github --memory ``` ## Topologies ### Mesh - All agents connect to all others - Best for: Research, exploration, brainstorming - Communication: High overhead, maximum information sharing ### Hierarchical - Tree structure with clear command chain - Best for: Development, structured tasks, large projects - Communication: Efficient, clear responsibilities ### Ring - Agents connect in a circle - Best for: Pipeline processing, sequential workflows - Communication: Low overhead, ordered processing ### Star - Central coordinator with satellite agents - Best for: Simple tasks, centralized control - Communication: Minimal overhead, clear coordination ## Integration with Claude Code Once initialized, use MCP tools in Claude Code: ```javascript mcp__claude-flow__swarm_init { topology: "hierarchical", maxAgents: 8 } ``` ## See Also - `agent spawn` - Create swarm agents - `task orchestrate` - Coordinate task execution - `swarm status` - Check swarm state - `swarm monitor` - Real-time monitoring