Strands Agents Samples

These samples demonstrate the Temporal Strands plugin, which runs Strands Agents inside Temporal Workflows. Model invocations, tool calls, and MCP tool calls all execute as Temporal Activities, so you get durable execution, Temporal-managed retries, and timeouts.

Samples

Sample	Description
hello_world	Minimal TemporalAgent invocation. Start here.
tools	Three tool patterns side by side: in-workflow @tool, custom @activity.defn wrapped via activity_as_tool, and a strands_tools tool wrapped as a Temporal activity.
human_in_the_loop	Pause a tool call on BeforeToolCallEvent.interrupt(), resume via Temporal signal. The canonical Strands HITL pattern.
activity_interrupt	Raise InterruptException from a Temporal activity to surface a HITL prompt across the activity boundary. Plugin-specific feature.
hooks	HookProvider with both an in-workflow callback and an activity_as_hook callback for I/O.
mcp	Connect to an MCP server (FastMCP echo) via TemporalMCPClient.
structured_output	Pydantic-typed agent output via structured_output_model.
streaming	Forward model chunks to an external subscriber via streaming_topic + WorkflowStream.
continue_as_new	Chat-style workflow that hands off agent.messages when history grows large.

Prerequisites

1. Install dependencies:

   uv sync --group strands-agents

   This installs the standalone temporalio-strands-agents package, which requires Temporal 1.34.0 or later.

2. Configure AWS credentials. The samples use the plugin's default BedrockModel(), which picks up the standard AWS SDK credential chain. Make sure the credentials grant access to a Bedrock model in your selected region (e.g., us-west-2).

   export AWS_REGION=us-west-2
   # plus AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY or an SSO profile

   You can pick a specific model by passing it to BedrockModel(model_id="...") in each sample's worker.

3. Start a local dev server with the Temporal CLI:

   temporal server start-dev

Running a Sample

Each sample has two scripts. Start the Worker first, then the Workflow starter in a separate terminal:

# Terminal 1: start the Worker
uv run strands_plugin/<sample>/run_worker.py

# Terminal 2: start the Workflow
uv run strands_plugin/<sample>/run_workflow.py

For example, to run the tools sample:

# Terminal 1
uv run strands_plugin/tools/run_worker.py

# Terminal 2
uv run strands_plugin/tools/run_workflow.py

Key Features Demonstrated

• Durable model invocation — every model call runs in an invoke_model activity with configurable timeouts and retries.
• Three ways to define tools — pure Strands @tool, custom Temporal activities, and ecosystem strands_tools wrapped as activities.
• Human-in-the-loop — both hook-based (BeforeToolCallEvent.interrupt()) and tool-body (raise InterruptException) styles.
• Hook system — deterministic in-workflow callbacks plus I/O callbacks dispatched via activity_as_hook.
• MCP integration — connect to MCP servers at worker startup; tool calls dispatched through per-server activities.
• Structured output — Pydantic-typed agent results via the plugin's pydantic_data_converter.
• Streaming — forward model chunks live to external subscribers.
• Long-lived chats — hand off agent.messages via continue-as-new to stay under Temporal's history limit.

Related

• Temporal Strands plugin docs
• Strands Agents