open-multi-agent
ActiveDescription
From a goal to a task DAG, automatically. TypeScript-native multi-agent orchestration with MCP and live tracing. Three runtime dependencies.
Key Features
- Goal-driven coordinator: a single runTeam() call decomposes goals into a task DAG and executes it automatically
- Mix any LLM providers in one team: 12 built-in providers plus any OpenAI-compatible endpoint (Ollama, vLLM, Groq, etc.)
- Extended thinking / reasoning support across Anthropic, Gemini, and OpenAI with cross-provider reasoning preservation
- Built-in tools + MCP integration: 6 filesystem and shell tools, plus full MCP client for external tool servers
- Three runtime modes: single agent (runAgent), auto-orchestrated team (runTeam), and explicit task pipeline (runTasks)
- Plan artifact support: preview DAGs before execution, save plans as version-controllable JSON, and replay without coordinator calls
Use Cases
💡 Multi-agent code generation with architect, developer, and reviewer roles collaborating on a REST API
💡 Automated software development workflows where goals are described in natural language and decomposed into executable task graphs
💡 Parallel task execution across independent sub-goals with automatic dependency resolution and load balancing
💡 Cross-provider AI pipelines where different agents use different LLM providers within the same team
Strengths & Limitations
✅ Strengths
- • Actively maintained, recent updates
- • High community interest (6.9k stars)
- • Permissive open-source license (MIT)
- • Responsive to issues, low backlog
Categories
Quick Start
npm install @open-multi-agent/core
import { OpenMultiAgent, type AgentConfig } from '@open-multi-agent/core'
const agents: AgentConfig[] = [
{ name: 'architect', model: 'claude-sonnet-4-6', systemPrompt: 'Design clean API contracts.', tools: ['file_write'] },
{ name: 'developer', model: 'claude-sonnet-4-6', systemPrompt: 'Implement runnable TypeScript.', tools: ['bash', 'file_read', 'file_write', 'file_edit'] },
]
const orchestrator = new OpenMultiAgent({ defaultModel: 'claude-sonnet-4-6' })
const team = orchestrator.createTeam('api-team', { name: 'api-team', agents, sharedMemory: true })
const result = await orchestrator.runTeam(team, 'Create a REST API for a todo list')