Build durable Java AI agents on Conductor. Agents can use local Java tools, wait for people, execute dynamic plans, and recover after a process restart because Conductor persists execution state.
New here? Follow Getting Started to configure a server-side LLM provider and run the maintained basic-agent example.
For an AI coding agent that understands Conductor operations, load Conductor Skills: npm install -g @conductor-oss/conductor-skills && conductor-skills --all.
Requirements: Java 21+ and a Conductor server.
dependencies {
implementation 'org.conductoross:conductor-client-ai:<VERSION>'
}Replace <VERSION> with a published version from Maven Central.
- Getting Started — configure a server and run a maintained agent example.
- Deploy · Serve · Run · Plan — choose the right runtime mode.
- Scheduling — schedule deployed agents with the shared typed client.
- Agents — builder API and
@AgentDef. - Tools — Java tools, HTTP/MCP tools, human approval, files, and credentials.
- Multi-Agent — sequential, parallel, handoff, swarm, and plan-execute agents.
- Guardrails, Termination, Callbacks, Stateful Agents, Streaming & Human-in-the-Loop, and Structured Output.
- Google ADK — bridge native ADK agents and sub-agent graphs.
- LangChain4j — turn existing
@ToolPOJOs andChatModelmetadata into Conductor agents. - LangGraph4j — run a native graph builder on the durable runtime.
- OpenAI Agents SDK style — use familiar tool and handoff shapes in Java.
- Spring Boot — auto-configured runtime and
@AgentDefdiscovery. - Runtime reference and control-plane reference.
- API map, agent-definition fields, and configuration schema.
- Control-plane example — deploy, start, inspect, stop, and cancel an agent.
| Capability | Conductor agent runtime |
|---|---|
| Process failure recovery | Durable workflow state resumes from completed work. |
| Java tools | Tools run as independently scalable Conductor worker tasks. |
| Long-running work | Human approval, schedules, and events do not hold application threads open. |
| Dynamic execution | Plans become durable sub-workflows that can be inspected and retried. |
| Observability | Inputs, outputs, tool calls, retries, and status share one execution record. |