open-multi-agent

From a goal to a task DAG, automatically. TypeScript-native multi-agent orchestration. Three runtime dependencies. 10 native LLM adapters · MCP · token budgets · retries · context compaction · live tracing.

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open-multi-agent is a multi-agent orchestration framework for TypeScript backends. Give it a goal; a coordinator agent decomposes it into a task DAG, parallelizes independents, and synthesizes the result. Three runtime dependencies, drops into any Node.js backend.

Your engineers describe the goal, not the graph.

A typical run, streamed live through onProgress:

agent_start coordinator
task_start design-api
task_complete design-api
task_start implement-handlers
task_start scaffold-tests         // independent tasks run in parallel
task_complete scaffold-tests
task_complete implement-handlers
task_start review-code            // unblocked after implementation
task_complete review-code
agent_complete coordinator        // synthesizes final result
Success: true
Tokens: 12847 output tokens

Features

Capability	What you get
Goal-driven coordinator	One runTeam(team, goal) call. The coordinator decomposes the goal into a task DAG, parallelizes independents, and synthesizes the result.
Mix providers in one team	10 native: Anthropic, OpenAI, Azure, Bedrock, Gemini, Grok, DeepSeek, MiniMax, Qiniu, Copilot. Ollama / vLLM / LM Studio / OpenRouter / Groq via OpenAI-compatible. (full list)
Tools + MCP	6 built-in (bash, file_*, grep, glob), opt-in delegate_to_agent, custom tools via defineTool() + Zod, any MCP server via connectMCPTools().
Streaming + structured output	Token-by-token streaming on every adapter; Zod-validated final answer with auto-retry on parse failure. (structured-output)
Observability	onProgress events, onTrace spans, post-run HTML dashboard rendering the executed task DAG. (trace-observability)
Pluggable shared memory	Default in-process KV; swap in Redis / Postgres / your own backend by implementing MemoryStore.

Production controls (context strategies, task retry with backoff, loop detection, tool output truncation/compression) are covered in the Production Checklist.

Quick Start

Requires Node.js >= 18.

Try it locally

Clone, install, run.

git clone https://github.com/JackChen-me/open-multi-agent && cd open-multi-agent
npm install
export ANTHROPIC_API_KEY=sk-...
npx tsx examples/basics/team-collaboration.ts

Three agents (architect, developer, reviewer) collaborate on a REST API in /tmp/express-api/. You watch the coordinator decompose the goal and run independent tasks in parallel as the progress events stream in.

Local models via Ollama need no API key, see providers/ollama. For other providers (OPENAI_API_KEY, GEMINI_API_KEY, etc.), check Supported Providers.

Use it in your project

npm install @jackchen_me/open-multi-agent

Three agents, one goal. The framework handles the rest:

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