base on A model-driven approach to building AI agents in just a few lines of code. <div align="center"> <div> <a href="https://strandsagents.com"> <img src="https://strandsagents.com/latest/assets/logo-github.svg" alt="Strands Agents" width="55px" height="105px"> </a> </div> <h1> Strands Agents </h1> <h2> A model-driven approach to building AI agents in just a few lines of code. </h2> <div align="center"> <a href="https://github.com/strands-agents/sdk-python/graphs/commit-activity"><img alt="GitHub commit activity" src="https://img.shields.io/github/commit-activity/m/strands-agents/sdk-python"/></a> <a href="https://github.com/strands-agents/sdk-python/issues"><img alt="GitHub open issues" src="https://img.shields.io/github/issues/strands-agents/sdk-python"/></a> <a href="https://github.com/strands-agents/sdk-python/pulls"><img alt="GitHub open pull requests" src="https://img.shields.io/github/issues-pr/strands-agents/sdk-python"/></a> <a href="https://github.com/strands-agents/sdk-python/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/github/license/strands-agents/sdk-python"/></a> <a href="https://pypi.org/project/strands-agents/"><img alt="PyPI version" src="https://img.shields.io/pypi/v/strands-agents"/></a> <a href="https://python.org"><img alt="Python versions" src="https://img.shields.io/pypi/pyversions/strands-agents"/></a> </div> <p> <a href="https://strandsagents.com/">Documentation</a> ◆ <a href="https://github.com/strands-agents/samples">Samples</a> ◆ <a href="https://github.com/strands-agents/sdk-python">Python SDK</a> ◆ <a href="https://github.com/strands-agents/tools">Tools</a> ◆ <a href="https://github.com/strands-agents/agent-builder">Agent Builder</a> ◆ <a href="https://github.com/strands-agents/mcp-server">MCP Server</a> </p> </div> Strands Agents is a simple yet powerful SDK that takes a model-driven approach to building and running AI agents. From simple conversational assistants to complex autonomous workflows, from local development to production deployment, Strands Agents scales with your needs. ## Feature Overview - **Lightweight & Flexible**: Simple agent loop that just works and is fully customizable - **Model Agnostic**: Support for Amazon Bedrock, Anthropic, LiteLLM, Llama, Ollama, OpenAI, Writer, and custom providers - **Advanced Capabilities**: Multi-agent systems, autonomous agents, and streaming support - **Built-in MCP**: Native support for Model Context Protocol (MCP) servers, enabling access to thousands of pre-built tools ## Quick Start ```bash # Install Strands Agents pip install strands-agents strands-agents-tools ``` ```python from strands import Agent from strands_tools import calculator agent = Agent(tools=[calculator]) agent("What is the square root of 1764") ``` > **Note**: For the default Amazon Bedrock model provider, you'll need AWS credentials configured and model access enabled for Claude 4 Sonnet in the us-west-2 region. See the [Quickstart Guide](https://strandsagents.com/) for details on configuring other model providers. ## Installation Ensure you have Python 3.10+ installed, then: ```bash # Create and activate virtual environment python -m venv .venv source .venv/bin/activate # On Windows use: .venv\Scripts\activate # Install Strands and tools pip install strands-agents strands-agents-tools ``` ## Features at a Glance ### Python-Based Tools Easily build tools using Python decorators: ```python from strands import Agent, tool @tool def word_count(text: str) -> int: """Count words in text. This docstring is used by the LLM to understand the tool's purpose. """ return len(text.split()) agent = Agent(tools=[word_count]) response = agent("How many words are in this sentence?") ``` **Hot Reloading from Directory:** Enable automatic tool loading and reloading from the `./tools/` directory: ```python from strands import Agent # Agent will watch ./tools/ directory for changes agent = Agent(load_tools_from_directory=True) response = agent("Use any tools you find in the tools directory") ``` ### MCP Support Seamlessly integrate Model Context Protocol (MCP) servers: ```python from strands import Agent from strands.tools.mcp import MCPClient from mcp import stdio_client, StdioServerParameters aws_docs_client = MCPClient( lambda: stdio_client(StdioServerParameters(command="uvx", args=["awslabs.aws-documentation-mcp-server@latest"])) ) with aws_docs_client: agent = Agent(tools=aws_docs_client.list_tools_sync()) response = agent("Tell me about Amazon Bedrock and how to use it with Python") ``` ### Multiple Model Providers Support for various model providers: ```python from strands import Agent from strands.models import BedrockModel from strands.models.ollama import OllamaModel from strands.models.llamaapi import LlamaAPIModel # Bedrock bedrock_model = BedrockModel( model_id="us.amazon.nova-pro-v1:0", temperature=0.3, streaming=True, # Enable/disable streaming ) agent = Agent(model=bedrock_model) agent("Tell me about Agentic AI") # Ollama ollama_model = OllamaModel( host="http://localhost:11434", model_id="llama3" ) agent = Agent(model=ollama_model) agent("Tell me about Agentic AI") # Llama API llama_model = LlamaAPIModel( model_id="Llama-4-Maverick-17B-128E-Instruct-FP8", ) agent = Agent(model=llama_model) response = agent("Tell me about Agentic AI") ``` Built-in providers: - [Amazon Bedrock](https://strandsagents.com/latest/user-guide/concepts/model-providers/amazon-bedrock/) - [Anthropic](https://strandsagents.com/latest/user-guide/concepts/model-providers/anthropic/) - [Cohere](https://strandsagents.com/latest/user-guide/concepts/model-providers/cohere/) - [LiteLLM](https://strandsagents.com/latest/user-guide/concepts/model-providers/litellm/) - [llama.cpp](https://strandsagents.com/latest/user-guide/concepts/model-providers/llamacpp/) - [LlamaAPI](https://strandsagents.com/latest/user-guide/concepts/model-providers/llamaapi/) - [MistralAI](https://strandsagents.com/latest/user-guide/concepts/model-providers/mistral/) - [Ollama](https://strandsagents.com/latest/user-guide/concepts/model-providers/ollama/) - [OpenAI](https://strandsagents.com/latest/user-guide/concepts/model-providers/openai/) - [SageMaker](https://strandsagents.com/latest/user-guide/concepts/model-providers/sagemaker/) - [Writer](https://strandsagents.com/latest/user-guide/concepts/model-providers/writer/) Custom providers can be implemented using [Custom Providers](https://strandsagents.com/latest/user-guide/concepts/model-providers/custom_model_provider/) ### Example tools Strands offers an optional strands-agents-tools package with pre-built tools for quick experimentation: ```python from strands import Agent from strands_tools import calculator agent = Agent(tools=[calculator]) agent("What is the square root of 1764") ``` It's also available on GitHub via [strands-agents/tools](https://github.com/strands-agents/tools). ## Documentation For detailed guidance & examples, explore our documentation: - [User Guide](https://strandsagents.com/) - [Quick Start Guide](https://strandsagents.com/latest/user-guide/quickstart/) - [Agent Loop](https://strandsagents.com/latest/user-guide/concepts/agents/agent-loop/) - [Examples](https://strandsagents.com/latest/examples/) - [API Reference](https://strandsagents.com/latest/api-reference/agent/) - [Production & Deployment Guide](https://strandsagents.com/latest/user-guide/deploy/operating-agents-in-production/) ## Contributing ❤️ We welcome contributions! See our [Contributing Guide](CONTRIBUTING.md) for details on: - Reporting bugs & features - Development setup - Contributing via Pull Requests - Code of Conduct - Reporting of security issues ## License This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details. ## Security See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information. ", Assign "at most 3 tags" to the expected json: {"id":"14668","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"