Open Multi Agent
From a goal to a task DAG, automatically. TypeScript-native multi-agent orchestration with MCP and live tracing. Three runtime dependencies.
What is Open Multi Agent?
Open Multi Agent is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to from a goal to a task dag, automatically. typescript-native multi-agent orchestration with mcp and live tracing. three runtime dependencies.
From a goal to a task DAG, automatically. TypeScript-native multi-agent orchestration with MCP and live tracing. Three runtime dependencies.
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- From a goal to a task DAG, automatically. TypeScript-native
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx open-multi-agentConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Open Multi Agent
Open Multi-Agent is a TypeScript-native orchestration framework that converts a high-level goal into a directed acyclic graph (DAG) of tasks and executes them with a coordinated team of AI agents. It supports twelve built-in LLM providers — including Anthropic, OpenAI, Gemini, DeepSeek, and local models via Ollama — while exposing filesystem tools, custom tool definitions, and the ability to consume any stdio-based MCP server. Developers use it to build autonomous pipelines where sub-agents collaborate, hand off work, and trace execution in a live HTML dashboard.
Prerequisites
- Node.js 18 or later installed
- At least one LLM provider API key (e.g., ANTHROPIC_API_KEY, OPENAI_API_KEY, or GEMINI_API_KEY)
- npm or npx available on your PATH
- An MCP client such as Claude Desktop or Claude Code if consuming via MCP
Install the core package
Add the @open-multi-agent/core package to your TypeScript or JavaScript project. Node.js 18+ is required.
npm install @open-multi-agent/coreSet your provider API key
Export the API key for your chosen LLM provider. Open Multi-Agent supports Anthropic, OpenAI, Gemini, Azure OpenAI, DeepSeek, Groq, Mistral, and many others.
export ANTHROPIC_API_KEY=sk-ant-your-key-here
# or
export OPENAI_API_KEY=sk-your-key-here
# or
export GEMINI_API_KEY=your-gemini-keyDefine an agent configuration
Create an AgentConfig object specifying the model to use and which built-in tools to grant. Tools are default-deny and must be explicitly listed.
import { AgentConfig } from '@open-multi-agent/core';
const agent: AgentConfig = {
name: 'developer',
model: 'claude-sonnet-4-6',
tools: ['bash', 'file_read', 'file_write', 'grep', 'glob'],
};Run a single agent or a full team
Use runAgent for a single focused task, or runTeam to automatically decompose a goal into a DAG of parallel and sequential sub-tasks.
import { Orchestrator } from '@open-multi-agent/core';
const orchestrator = new Orchestrator();
// Single agent
await orchestrator.runAgent(agent, 'Refactor auth.ts to use async/await');
// Auto-DAG team run
await orchestrator.runTeam(team, 'Build a REST API with tests and documentation');Connect an MCP server as a tool source
Open Multi-Agent can consume any stdio-based MCP server, making its tools available to agents in your pipeline.
import { connectMCPTools } from '@open-multi-agent/core';
const mcpTools = await connectMCPTools({
command: 'npx',
args: ['-y', '@wonderwhy-er/desktop-commander@latest'],
});
const agent: AgentConfig = {
name: 'file-agent',
model: 'claude-sonnet-4-6',
tools: [...mcpTools],
};Configure resource limits and observability
Set token budgets, timeouts, retry counts, and context strategies to make long-running pipelines reliable. Enable onProgress and onTrace callbacks for live observability.
const orchestrator = new Orchestrator({
maxTokenBudget: 100000,
timeoutMs: 300000,
maxRetries: 3,
retryDelayMs: 2000,
contextStrategy: 'summarize',
onProgress: (event) => console.log(event),
});Open Multi Agent Examples
Client configuration
Open Multi-Agent is a framework library, not an MCP server itself. Use it in a Node.js script that you run directly. Here is a minimal package.json and entry point.
// package.json
{
"name": "my-agent-pipeline",
"type": "module",
"scripts": { "start": "node agent.js" },
"dependencies": { "@open-multi-agent/core": "latest" }
}
// agent.js
import { Orchestrator } from '@open-multi-agent/core';
const orch = new Orchestrator();
await orch.runAgent(
{ name: 'coder', model: 'claude-sonnet-4-6', tools: ['file_read', 'file_write', 'bash'] },
process.argv[2] || 'List all TypeScript files in src/'
);Prompts to try
These goal strings work well as the prompt argument to runAgent or runTeam.
- "Analyse the performance bottlenecks in src/ and suggest optimisations"
- "Write unit tests for all exported functions in lib/utils.ts"
- "Create a three-agent pipeline: researcher, writer, and reviewer to produce a technical blog post about MCP"
- "Decompose building a Node.js CLI tool into parallel tasks and execute them"Troubleshooting Open Multi Agent
Error: model not found or API key invalid
Ensure the correct environment variable is exported for your provider (e.g., ANTHROPIC_API_KEY for claude-* models). Run `echo $ANTHROPIC_API_KEY` to confirm the variable is set in the current shell.
Agents exceed token budget and stop early
Increase maxTokenBudget in the Orchestrator config, or set contextStrategy to 'summarize' or 'compact' to compress conversation history between turns.
MCP tools not available to agents after connectMCPTools
Confirm the MCP server process starts successfully by running its command manually (e.g., npx -y @wonderwhy-er/desktop-commander@latest). Spread the returned tools array into the agent's tools field rather than assigning it directly.
Frequently Asked Questions about Open Multi Agent
What is Open Multi Agent?
Open Multi Agent is a Model Context Protocol (MCP) server that from a goal to a task dag, automatically. typescript-native multi-agent orchestration with mcp and live tracing. three runtime dependencies. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Open Multi Agent?
Follow the installation instructions on the Open Multi Agent GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Open Multi Agent?
Open Multi Agent works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Open Multi Agent free to use?
Yes, Open Multi Agent is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
Open Multi Agent Alternatives — Similar Coding Agents Servers
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Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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