# Agentfield

> Control plane for autonomous AI agents that treats agents as production-grade microservices with built-in cryptographic identity, observability, orchestration, and SDKs for Python, TypeScript, and Go.

Agentfield provides a control plane for building, deploying, and operating autonomous AI agents as production-grade microservices. It gives every agent a cryptographic identity (DID) and issues verifiable credentials for tamper-proof audit trails, while exposing auto-generated APIs and runtime observability. The platform supports long-running asynchronous workflows, secure inter-agent communication, zero-config shared memory, and built-in deployment primitives to run agent fleets at scale.

- **Agents as microservices** — Write reasoners and skills as typed functions; each becomes an auto-generated REST API endpoint and OpenAPI spec.
- **Cryptographic identity & verifiable credentials** — Each agent receives a DID and every execution can produce a signed verifiable credential for audit and compliance.
- **Async execution & webhooks** — Support for long-running tasks (hours/days) with async execution models and webhook callbacks for completion events.
- **Secure inter-agent calls** — Built-in, identity-verified ctx.call-style RPC with automatic discovery and load balancing between agent instances.
- **Shared memory & vector search** — Zero-config distributed memory fabric with semantic/vector search capabilities to share context across agents.
- **Observability & production operations** — Auto-generated health probes, metrics, retry policies, webhooks, and workflow DAG tracing out of the box.
- **Multi-language SDKs and real-time APIs** — Python, TypeScript, and Go SDKs plus REST, WebSocket, and Server-Sent Events for streaming and real-time progress updates.

Get started by cloning or installing the source, using a provided SDK to define an agent function, and deploying the agent node (container/Kubernetes-ready). Call agents via the generated REST endpoints or SDKs, monitor workflows and audit trails, and extend with custom webhooks and integrations.

## Features
- Auto-generated OpenAPI endpoints for each agent
- Cryptographic DIDs and verifiable credentials for every execution
- Long-running async workflows with webhook callbacks
- Zero-config distributed shared memory with vector search
- Automatic service discovery, routing, and load balancing
- Python, TypeScript, and Go SDKs plus REST and real-time APIs
- Production-ready probes, retries, metrics, and DAG tracing
- Open source (Apache 2.0) with CLI tooling

## Integrations
Kubernetes, Docker, OpenAPI, Webhooks, CLI, GitHub, MCP integration

## Platforms
MACOS, LINUX, WEB, API, DEVELOPER_SDK

## Pricing
Open Source

## Links
- Website: https://www.agentfield.ai/
- Documentation: https://www.agentfield.ai/docs
- Repository: https://github.com/Agent-Field/agentfield
- EveryDev.ai: https://www.everydev.ai/tools/agentfield