Strands Agents Typescript SDK
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    Class Agent

    Orchestrates the interaction between a model, a set of tools, and MCP clients. The Agent is responsible for managing the lifecycle of tools and clients and invoking the core decision-making loop.

    Implements

    Index

    Constructors

    Properties

    messages: Message[]

    The conversation history of messages between user and assistant.

    state: AgentState

    Agent state storage accessible to tools and application logic. State is not passed to the model during inference.

    conversationManager: HookProvider

    Conversation manager for handling message history and context overflow.

    Hook registry for managing event callbacks. Hooks enable observing and extending agent behavior.

    model: Model

    The model provider used by the agent for inference.

    systemPrompt?: SystemPrompt

    The system prompt to pass to the model provider.

    Accessors

    Methods

    • Invokes the agent and returns the final result.

      This is a convenience method that consumes the stream() method and returns only the final AgentResult. Use stream() if you need access to intermediate streaming events.

      Parameters

      • args: InvokeArgs

        Arguments for invoking the agent

      Returns Promise<AgentResult>

      Promise that resolves to the final AgentResult

      const agent = new Agent({ model, tools })
      const result = await agent.invoke('What is 2 + 2?')
      console.log(result.lastMessage) // Agent's response
    • Streams the agent execution, yielding events and returning the final result.

      The agent loop manages the conversation flow by:

      1. Streaming model responses and yielding all events
      2. Executing tools when the model requests them
      3. Continuing the loop until the model completes without tool use

      Use this method when you need access to intermediate streaming events. For simple request/response without streaming, use invoke() instead.

      An explicit goal of this method is to always leave the message array in a way that the agent can be reinvoked with a user prompt after this method completes. To that end assistant messages containing tool uses are only added after tool execution succeeds with valid toolResponses

      Parameters

      • args: InvokeArgs

        Arguments for invoking the agent

      Returns AsyncGenerator<AgentStreamEvent, AgentResult, undefined>

      Async generator that yields AgentStreamEvent objects and returns AgentResult

      const agent = new Agent({ model, tools })

      for await (const event of agent.stream('Hello')) {
      console.log('Event:', event.type)
      }
      // Messages array is mutated in place and contains the full conversation