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AgentField

Build, run and scale AI agents like APIs and microservices — observable and identity-aware from day one

★ 2,264 GitHub Apache-2.0 agentmulti-agentai-backendmicroservicescloud-native AI Agents

Overview

AgentField is an open-source platform for building, running, and scaling AI agents as if they were APIs and microservices. Unlike traditional agent frameworks that treat agents as monolithic scripts, AgentField provides a cloud-native architecture with built-in identity management, authentication, observability, and horizontal scaling. Agents are deployed as independent services with their own identity, can be orchestrated through a control plane, and integrate seamlessly with existing infrastructure. Built in Go with TypeScript/Python SDKs, it supports multi-agent systems, RAG pipelines, and enterprise-grade deployment.

Requirements

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  agentfield:
    image: agentfield/control-plane:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/agentfield:/data

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Guides & articles

Deploying AgentField with Docker: Build a Multi-Agent Research Pipeline

Step-by-step tutorial for running AgentField with Docker, creating agents with identities, and building a multi-agent research pipeline.

Jul 4, 2026

AgentField: Build, Run and Scale AI Agents Like Microservices

AgentField is an open-source platform that treats AI agents as cloud-native services with identity, auth, and observability built in.

Jul 4, 2026