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https://github.com/strands-agents/tools

A set of tools that gives agents powerful capabilities.
https://github.com/strands-agents/tools

agentic agentic-ai agents ai anthropic autonomous-agents bedrock genai litellm llama llm machine-learning mcp multi-agent-systems ollama openai opentelemetry python

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A set of tools that gives agents powerful capabilities.

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README 

          


  


    

      Strands Agents

    

  



  


    Strands Agents Tools

  



  


    A model-driven approach to building AI agents in just a few lines of code.

  



  


    GitHub commit activity

    GitHub open issues

    GitHub open pull requests

    License

    PyPI version

    Python versions

  


  

  


    Documentation

    ◆ Samples

    ◆ Python SDK

    ◆ Tools

    ◆ Agent Builder

    ◆ MCP Server

  





Strands Agents Tools provides a powerful set of tools for your agents to use. It bridges the gap between large language models and practical applications by offering ready-to-use tools for file operations, system execution, API interactions, mathematical operations, and more.



## ✨ Features



- 📁 **File Operations** - Read, write, and edit files with syntax highlighting and intelligent modifications

- 🖥️ **Shell Integration** - Execute and interact with shell commands securely

- 🧠 **Memory** - Store user and agent memories across agent runs to provide personalized experiences with both Mem0 and Amazon Bedrock Knowledge Bases

- 🌐 **HTTP Client** - Make API requests with comprehensive authentication support

- 💬 **Slack Client** - Real-time Slack events, message processing, and Slack API access

- 🐍 **Python Execution** - Run Python code snippets with state persistence, user confirmation for code execution, and safety features

- 🧮 **Mathematical Tools** - Perform advanced calculations with symbolic math capabilities

- ☁️ **AWS Integration** - Seamless access to AWS services

- 🖼️ **Image Processing** - Generate and process images for AI applications

- 🎥 **Video Processing** - Use models and agents to generate dynamic videos

- 🎙️ **Audio Output** - Enable models to generate audio and speak

- 🔄 **Environment Management** - Handle environment variables safely

- 📝 **Journaling** - Create and manage structured logs and journals

- ⏱️ **Task Scheduling** - Schedule and manage cron jobs

- 🧠 **Advanced Reasoning** - Tools for complex thinking and reasoning capabilities

- 🐝 **Swarm Intelligence** - Coordinate multiple AI agents for parallel problem solving with shared memory

- 🔄 **Multiple tools in Parallel**  - Call multiple other tools at the same time in parallel with Batch Tool

  

## 📦 Installation



### Quick Install



```bash

pip install strands-agents-tools

```



To install the dependencies for optional tools:



```bash

pip install strands-agents-tools[mem0_memory]

```



### Development Install



```bash

# Clone the repository

git clone https://github.com/strands-agents/tools.git

cd tools



# Create and activate virtual environment

python3 -m venv .venv

source .venv/bin/activate  # On Windows: venv\Scripts\activate



# Install in development mode

pip install -e ".[dev]"



# Install pre-commit hooks

pre-commit install

```



### Tools Overview



Below is a comprehensive table of all available tools, how to use them with an agent, and typical use cases:



| Tool | Agent Usage | Use Case |

|------|-------------|----------|

| file_read | `agent.tool.file_read(path="path/to/file.txt")` | Reading configuration files, parsing code files, loading datasets |

| file_write | `agent.tool.file_write(path="path/to/file.txt", content="file content")` | Writing results to files, creating new files, saving output data |

| editor | `agent.tool.editor(command="view", path="path/to/file.py")` | Advanced file operations like syntax highlighting, pattern replacement, and multi-file edits |

| shell* | `agent.tool.shell(command="ls -la")` | Executing shell commands, interacting with the operating system, running scripts |

| http_request | `agent.tool.http_request(method="GET", url="https://api.example.com/data")` | Making API calls, fetching web data, sending data to external services |

| python_repl* | `agent.tool.python_repl(code="import pandas as pd\ndf = pd.read_csv('data.csv')\nprint(df.head())")` | Running Python code snippets, data analysis, executing complex logic with user confirmation for security |

| calculator | `agent.tool.calculator(expression="2 * sin(pi/4) + log(e**2)")` | Performing mathematical operations, symbolic math, equation solving |

| use_aws | `agent.tool.use_aws(service_name="s3", operation_name="list_buckets", parameters={}, region="us-west-2")` | Interacting with AWS services, cloud resource management |

| retrieve | `agent.tool.retrieve(text="What is STRANDS?")` | Retrieving information from Amazon Bedrock Knowledge Bases |

| nova_reels | `agent.tool.nova_reels(action="create", text="A cinematic shot of mountains", s3_bucket="my-bucket")` | Create high-quality videos using Amazon Bedrock Nova Reel with configurable parameters via environment variables |

| mem0_memory | `agent.tool.mem0_memory(action="store", content="Remember I like to tennis", user_id="alex")` | Store user and agent memories across agent runs to provide personalized experience |

| memory | `agent.tool.memory(action="retrieve", query="product features")` | Store, retrieve, list, and manage documents in Amazon Bedrock Knowledge Bases with configurable parameters via environment variables |

| environment | `agent.tool.environment(action="list", prefix="AWS_")` | Managing environment variables, configuration management |

| generate_image | `agent.tool.generate_image(prompt="A sunset over mountains")` | Creating AI-generated images for various applications |

| image_reader | `agent.tool.image_reader(image_path="path/to/image.jpg")` | Processing and reading image files for AI analysis |

| journal | `agent.tool.journal(action="write", content="Today's progress notes")` | Creating structured logs, maintaining documentation |

| think | `agent.tool.think(thought="Complex problem to analyze", cycle_count=3)` | Advanced reasoning, multi-step thinking processes |

| load_tool | `agent.tool.load_tool(path="path/to/custom_tool.py", name="custom_tool")` | Dynamically loading custom tools and extensions |

| swarm | `agent.tool.swarm(task="Analyze this problem", swarm_size=3, coordination_pattern="collaborative")` | Coordinating multiple AI agents to solve complex problems through collective intelligence |

| current_time | `agent.tool.current_time(timezone="US/Pacific")` | Get the current time in ISO 8601 format for a specified timezone |

| sleep | `agent.tool.sleep(seconds=5)` | Pause execution for the specified number of seconds, interruptible with SIGINT (Ctrl+C) |

| agent_graph | `agent.tool.agent_graph(agents=["agent1", "agent2"], connections=[{"from": "agent1", "to": "agent2"}])` | Create and visualize agent relationship graphs for complex multi-agent systems |

| cron* | `agent.tool.cron(action="schedule", name="task", schedule="0 * * * *", command="backup.sh")` | Schedule and manage recurring tasks with cron job syntax 
 **Does not work on Windows |

| slack | `agent.tool.slack(action="post_message", channel="general", text="Hello team!")` | Interact with Slack workspace for messaging and monitoring |

| speak | `agent.tool.speak(text="Operation completed successfully", style="green", mode="polly")` | Output status messages with rich formatting and optional text-to-speech |

| stop | `agent.tool.stop(message="Process terminated by user request")` | Gracefully terminate agent execution with custom message |

| use_llm | `agent.tool.use_llm(prompt="Analyze this data", system_prompt="You are a data analyst")` | Create nested AI loops with customized system prompts for specialized tasks |

| workflow | `agent.tool.workflow(action="create", name="data_pipeline", steps=[{"tool": "file_read"}, {"tool": "python_repl"}])` | Define, execute, and manage multi-step automated workflows |

| batch| `agent.tool.batch(invocations=[{"name": "current_time", "arguments": {"timezone": "Europe/London"}}, {"name": "stop", "arguments": {}}])` | Call multiple other tools in parallel. |



\* *These tools do not work on windows*



## 💻 Usage Examples



### File Operations



```python

from strands import Agent

from strands_tools import file_read, file_write, editor



agent = Agent(tools=[file_read, file_write, editor])



agent.tool.file_read(path="config.json")

agent.tool.file_write(path="output.txt", content="Hello, world!")

agent.tool.editor(command="view", path="script.py")

```



### Shell Commands



*Note: `shell` does not work on Windows.*



```python

from strands import Agent

from strands_tools import shell



agent = Agent(tools=[shell])



# Execute a single command

result = agent.tool.shell(command="ls -la")



# Execute a sequence of commands

results = agent.tool.shell(command=["mkdir -p test_dir", "cd test_dir", "touch test.txt"])



# Execute commands with error handling

agent.tool.shell(command="risky-command", ignore_errors=True)

```



### HTTP Requests



```python

from strands import Agent

from strands_tools import http_request



agent = Agent(tools=[http_request])



# Make a simple GET request

response = agent.tool.http_request(

    method="GET",

    url="https://api.example.com/data"

)



# POST request with authentication

response = agent.tool.http_request(

    method="POST",

    url="https://api.example.com/resource",

    headers={"Content-Type": "application/json"},

    body=json.dumps({"key": "value"}),

    auth_type="Bearer",

    auth_token="your_token_here"

)

```



### Python Code Execution



*Note: `python_repl` does not work on Windows.*



```python

from strands import Agent

from strands_tools import python_repl



agent = Agent(tools=[python_repl])



# Execute Python code with state persistence

result = agent.tool.python_repl(code="""

import pandas as pd



# Load and process data

data = pd.read_csv('data.csv')

processed = data.groupby('category').mean()



processed.head()

""")

```



### Swarm Intelligence



```python

from strands import Agent

from strands_tools import swarm



agent = Agent(tools=[swarm])



# Create a collaborative swarm of agents to tackle a complex problem

result = agent.tool.swarm(

    task="Generate creative solutions for reducing plastic waste in urban areas",

    swarm_size=5,

    coordination_pattern="collaborative"

)



# Create a competitive swarm for diverse solution generation

result = agent.tool.swarm(

    task="Design an innovative product for smart home automation",

    swarm_size=3,

    coordination_pattern="competitive"

)



# Hybrid approach combining collaboration and competition

result = agent.tool.swarm(

    task="Develop marketing strategies for a new sustainable fashion brand",

    swarm_size=4,

    coordination_pattern="hybrid"

)

```



### Use AWS



```python

from strands import Agent

from strands_tools import use_aws



agent = Agent(tools=[use_aws])



# List S3 buckets

result = agent.tool.use_aws(

    service_name="s3",

    operation_name="list_buckets",

    parameters={},

    region="us-east-1",

    label="List all S3 buckets"

)



# Get the contents of a specific S3 bucket

result = agent.tool.use_aws(

    service_name="s3",

    operation_name="list_objects_v2",

    parameters={"Bucket": "example-bucket"},  # Replace with your actual bucket name

    region="us-east-1",

    label="List objects in a specific S3 bucket"

)



# Get the list of EC2 subnets

result = agent.tool.use_aws(

    service_name="ec2",

    operation_name="describe_subnets",

    parameters={},

    region="us-east-1",

    label="List all subnets"

)

```



### Batch Tool



```python

import os

import sys



from strands import Agent

from strands_tools import batch, http_request, use_aws



# Example usage of the batch with http_request and use_aws tools

agent = Agent(tools=[batch, http_request, use_aws])



result = agent.tool.batch(

    invocations=[

        {"name": "http_request", "arguments": {"method": "GET", "url": "https://api.ipify.org?format=json"}},

        {

            "name": "use_aws",

            "arguments": {

                "service_name": "s3",

                "operation_name": "list_buckets",

                "parameters": {},

                "region": "us-east-1",

                "label": "List S3 Buckets"

            }

        },

    ]

)

```



## 🌍 Environment Variables Configuration



Agents Tools provides extensive customization through environment variables. This allows you to configure tool behavior without modifying code, making it ideal for different environments (development, testing, production).



### Global Environment Variables



These variables affect multiple tools:



| Environment Variable | Description | Default | Affected Tools |

|----------------------|-------------|---------|---------------|

| BYPASS_TOOL_CONSENT | Bypass consent for tool invocation, set to "true" to enable | false | All tools that require consent (e.g. shell, file_write, python_repl) |

| STRANDS_TOOL_CONSOLE_MODE | Enable rich UI for tools, set to "enabled" to enable | disabled | All tools that have optional rich UI |

| AWS_REGION | Default AWS region for AWS operations | us-west-2 | use_aws, retrieve, generate_image, memory, nova_reels |

| AWS_PROFILE | AWS profile name to use from ~/.aws/credentials | default | use_aws, retrieve |

| LOG_LEVEL | Logging level (DEBUG, INFO, WARNING, ERROR) | INFO | All tools |



### Tool-Specific Environment Variables



#### Calculator Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| CALCULATOR_MODE | Default calculation mode | evaluate |

| CALCULATOR_PRECISION | Number of decimal places for results | 10 |

| CALCULATOR_SCIENTIFIC | Whether to use scientific notation for numbers | False |

| CALCULATOR_FORCE_NUMERIC | Force numeric evaluation of symbolic expressions | False |

| CALCULATOR_FORCE_SCIENTIFIC_THRESHOLD | Threshold for automatic scientific notation | 1e21 |

| CALCULATOR_DERIVE_ORDER | Default order for derivatives | 1 |

| CALCULATOR_SERIES_POINT | Default point for series expansion | 0 |

| CALCULATOR_SERIES_ORDER | Default order for series expansion | 5 |



#### Current Time Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| DEFAULT_TIMEZONE | Default timezone for current_time tool | UTC |



#### Sleep Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| MAX_SLEEP_SECONDS | Maximum allowed sleep duration in seconds | 300 |



#### Mem0 Memory Tool



The Mem0 Memory Tool supports three different backend configurations:



1. **Mem0 Platform**:

   - Uses the Mem0 Platform API for memory management

   - Requires a Mem0 API key



2. **OpenSearch** (Recommended for AWS environments):

   - Uses OpenSearch as the vector store backend

   - Requires AWS credentials and OpenSearch configuration



3. **FAISS** (Default for local development):

   - Uses FAISS as the local vector store backend

   - Requires faiss-cpu package for local vector storage



| Environment Variable | Description | Default | Required For |

|----------------------|-------------|---------|--------------|

| MEM0_API_KEY | Mem0 Platform API key | None | Mem0 Platform |

| OPENSEARCH_HOST | OpenSearch Host URL | None | OpenSearch |

| AWS_REGION | AWS Region for OpenSearch | us-west-2 | OpenSearch |

| DEV | Enable development mode (bypasses confirmations) | false | All modes |



**Note**:

- If `MEM0_API_KEY` is set, the tool will use the Mem0 Platform

- If `OPENSEARCH_HOST` is set, the tool will use OpenSearch

- If neither is set, the tool will default to FAISS (requires `faiss-cpu` package)



#### Memory Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| MEMORY_DEFAULT_MAX_RESULTS | Default maximum results for list operations | 50 |

| MEMORY_DEFAULT_MIN_SCORE | Default minimum relevance score for filtering results | 0.4 |

#### Nova Reels Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| NOVA_REEL_DEFAULT_SEED | Default seed for video generation | 0 |

| NOVA_REEL_DEFAULT_FPS | Default frames per second for generated videos | 24 |

| NOVA_REEL_DEFAULT_DIMENSION | Default video resolution in WIDTHxHEIGHT format | 1280x720 |

| NOVA_REEL_DEFAULT_MAX_RESULTS | Default maximum number of jobs to return for list action | 10 |



#### Python REPL Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| PYTHON_REPL_BINARY_MAX_LEN | Maximum length for binary content before truncation | 100 |



#### Shell Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| SHELL_DEFAULT_TIMEOUT | Default timeout in seconds for shell commands | 900 |



#### Slack Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| SLACK_DEFAULT_EVENT_COUNT | Default number of events to retrieve | 42 |

| STRANDS_SLACK_AUTO_REPLY | Enable automatic replies to messages | false |

| STRANDS_SLACK_LISTEN_ONLY_TAG | Only process messages containing this tag | None |



#### Speak Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| SPEAK_DEFAULT_STYLE | Default style for status messages | green |

| SPEAK_DEFAULT_MODE | Default speech mode (fast/polly) | fast |

| SPEAK_DEFAULT_VOICE_ID | Default Polly voice ID | Joanna |

| SPEAK_DEFAULT_OUTPUT_PATH | Default audio output path | speech_output.mp3 |

| SPEAK_DEFAULT_PLAY_AUDIO | Whether to play audio by default | True |



#### Editor Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| EDITOR_DIR_TREE_MAX_DEPTH | Maximum depth for directory tree visualization | 2 |

| EDITOR_DEFAULT_STYLE | Default style for output panels | default |

| EDITOR_DEFAULT_LANGUAGE | Default language for syntax highlighting | python |



#### Environment Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| ENV_VARS_MASKED_DEFAULT | Default setting for masking sensitive values | true |



#### File Read Tool



| Environment Variable | Description | Default | 

|----------------------|-------------|---------|

| FILE_READ_RECURSIVE_DEFAULT | Default setting for recursive file searching | true |

| FILE_READ_CONTEXT_LINES_DEFAULT | Default number of context lines around search matches | 2 |

| FILE_READ_START_LINE_DEFAULT | Default starting line number for lines mode | 0 |

| FILE_READ_CHUNK_OFFSET_DEFAULT | Default byte offset for chunk mode | 0 |

| FILE_READ_DIFF_TYPE_DEFAULT | Default diff type for file comparisons | unified |

| FILE_READ_USE_GIT_DEFAULT | Default setting for using git in time machine mode | true |

| FILE_READ_NUM_REVISIONS_DEFAULT | Default number of revisions to show in time machine mode | 5 |



## 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.



## ⚠️ Preview Status



Strands Agents is currently in public preview. During this period:

- APIs may change as we refine the SDK

- We welcome feedback and contributions