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Strands Agents SDK

Strands Agents SDK

Section titled “Strands Agents SDK”

=== “Python”

[Strands Agents]({{ py_sdk_repo_home }}) is a simple-to-use, code-first framework for building agents.


First, install the Strands Agents SDK:


```bash
pip install strands-agents
```

=== “TypeScript”

[Strands Agents]({{ ts_sdk_repo_home }}) is a simple-to-use, code-first framework for building agents.


First, install the Strands Agents SDK:


```bash
npm install @strands-agents/sdk
```

Then create your first agent:

=== “Python”

Create a file called `agent.py`:


```python
from strands import Agent


# Create an agent with default settings
agent = Agent()


# Ask the agent a question
agent("Tell me about agentic AI")
```

=== “TypeScript”

Create a file called `agent.ts`:


```typescript
// Create a basic agent
import { Agent } from '@strands-agents/sdk'


// Create an agent with default settings
const agent = new Agent();


// Ask the agent a question
const response = await agent.invoke("Tell me about agentic AI");
console.log(response.lastMessage);
```

Now run the agent:

=== “Python”

```bash
python -u agent.py
```

=== “TypeScript”

```bash
npx tsx agent.ts
```

That’s it!

Note: To run this example hello world agent you will need to set up credentials for our model provider and enable model access. The default model provider is Amazon Bedrock and the default model is Claude 4 Sonnet inference model from the region of your credentials. For example, if you set the region to us-east-1 then the default model id will be: us.anthropic.claude-sonnet-4-20250514-v1:0.

For the default Amazon Bedrock model provider, see the Boto3 documentation for Python or TypeScript to set up AWS credentials. Typically for development, AWS credentials are defined in AWS_ prefixed environment variables or configured with aws configure. You will also need to enable Claude 4 Sonnet model access in Amazon Bedrock, following the AWS documentation to enable access.

Different model providers can be configured for agents by following the quickstart guide.

See Bedrock troubleshooting if you encounter any issues.

Features

Section titled “Features”

Strands Agents is lightweight and production-ready, supporting many model providers and deployment targets.

Key features include:

  • Lightweight and gets out of your way: A simple agent loop that just works and is fully customizable.
  • Production ready: Full observability, tracing, and deployment options for running agents at scale.
  • Model, provider, and deployment agnostic: Strands supports many different models from many different providers.
  • Community-driven tools: Get started quickly with a powerful set of community-contributed tools for a broad set of capabilities.
  • Multi-agent and autonomous agents: Apply advanced techniques to your AI systems like agent teams and agents that improve themselves over time.
  • Conversational, non-conversational, streaming, and non-streaming: Supports all types of agents for various workloads.
  • Safety and security as a priority: Run agents responsibly while protecting data.

Next Steps

Section titled “Next Steps”

Ready to learn more? Check out these resources:

  • Quickstart - A more detailed introduction to Strands Agents
  • Examples - Examples for many use cases, types of agents, multi-agent systems, autonomous agents, and more
  • Community Supported Tools - The {{ link_strands_tools }} package is a community-driven project that provides a powerful set of tools for your agents to use
  • [Strands Agent Builder]({{ agent_builder_repo_home }}) - Use the accompanying {{ link_strands_builder }} agent builder to harness the power of LLMs to generate your own tools and agents

!!! tip “Join Our Community”

Learn how to contribute to our [Python]({{ py_sdk_repo_home }}/CONTRIBUTING.md) or [TypeScript]({{ ts_sdk_repo_home }}/CONTRIBUTING.md) SDKs, or join our community discussions to shape the future of Strands Agents ❤️.