agentfield
Build, run and scale AI agents like API and microservices
AgentField is an open-source AI agent control plane that transforms agent functions written in Python, Go, or TypeScript into production-ready REST APIs with built-in orchestration, memory, and observability. It enables developers to build agents that call each other through a service mesh, automatically handling routing, retries, distributed fan-out, and execution tracing. The platform supports massive scale (10,000+ coordinated agents per workflow), includes cryptographic identity and governance, and provides features like human-in-the-loop approvals, canary deployments, and multi-turn coding agent integration. AgentField bridges the gap between agent development frameworks and production infrastructure, offering the runtime layer that makes AI agents callable, durable, and observable in real-world systems.
Key Features
Use Cases
- 01Building multi-agent research systems that recursively spawn thousands of parallel agents for deep analysis
- 02Creating autonomous engineering teams where PM, architect, coder, and QA agents coordinate to build features
- 03Implementing insurance claims processing with AI evaluation, risk scoring, and mandatory human approvals
- 04Deploying security audit agents that trace vulnerabilities source-to-sink across 250+ coordinated reviewers
- 05Setting up reactive database intelligence where MongoDB triggers invoke agents for real-time enrichment
- 06Running agentic code review systems that analyze PRs with custom strategies and adversarial verification
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agentfield — FAQ
What is AgentField?+
AgentField is an open-source control plane that provides production infrastructure for AI agents, turning simple Python, Go, or TypeScript functions into scalable REST APIs with routing, memory, observability, and governance. It's the runtime layer between agent development frameworks and production deployment.
How do I install AgentField?+
Run 'curl -fsSL https://agentfield.ai/install.sh | bash' to install the control plane and CLI. Then use 'af init my-agent --defaults' to scaffold a new agent, or 'af install <repo-url>' to deploy existing agent nodes. Start the control plane with 'af server' and agents auto-register on startup.
Which clients and frameworks work with AgentField?+
AgentField integrates with coding agents like Claude Code, Codex, Gemini CLI, OpenCode, Cursor, and Windsurf for prompt-to-production workflows. It also works alongside existing frameworks like LangChain, CrewAI, and PydanticAI—you can run their logic inside AgentField reasoners to add production capabilities.
Do I need API keys to use AgentField?+
The AgentField control plane itself requires no API keys. However, agents that call LLMs will need keys for your chosen providers (OpenAI, Anthropic, OpenRouter, etc.). The 'af install' command prompts once for shared secrets and stores them encrypted for reuse across nodes.
Is AgentField free and open source?+
Yes, AgentField is licensed under Apache 2.0 and fully open source. All core features including the control plane, SDKs, memory, identity, and observability are free to use in both development and production.
What makes AgentField different from agent frameworks like LangChain?+
Frameworks help you write agent logic; AgentField runs it in production. It provides the infrastructure layer for routing, async execution, cross-agent calls, distributed memory, human approvals, canary deployments, and cryptographic audit trails—capabilities you'd otherwise build from scratch with queues and microservices.
How do I install agentfield?+
Open the source repository on GitHub and follow its README. agentfield is a agent — MCP Agents Market links you directly to the official repo.
Is agentfield free?+
agentfield is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.