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.
pip install strands-agents-toolsTo install the dependencies for optional tools:
pip install strands-agents-tools[mem0_memory]# 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 installBelow 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 play 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_stability | agent.tool.generate_image_stability(prompt="A tranquil pool") | Creating images using Stability AI models |
| 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 <br> **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. |
| use_browser | agent.tool.use_browser(action="navigate", url="https://www.example.com") | Web scraping, automated testing, form filling, web automation tasks |
* These tools do not work on windows
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")Note: shell does not work on Windows.
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)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"
)Note: python_repl does not work on Windows.
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()
""")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"
)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"
)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"
}
},
]
)from strands import Agent
from strands_tools import use_browser
agent = Agent(tools=[use_browser])
# Simple navigation
result = agent.tool.use_browser(action="navigate", url="https://example.com")
# Sequential actions for form filling
result = agent.tool.use_browser(actions=[
{"action": "navigate", "args": {"url": "https://example.com/login"}},
{"action": "type", "args": {"selector": "#username", "text": "[email protected]"}},
{"action": "click", "args": {"selector": "#submit"}}
])
# Web scraping with content extraction
result = agent.tool.use_browser(actions=[
{"action": "navigate", "args": {"url": "https://example.com/data"}},
{"action": "get_text", "args": {"selector": ".content"}},
{"action": "click", "args": {"selector": ".next-page"}},
{"action": "get_html", "args": {"selector": "main"}}
])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).
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 |
| 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 |
| Environment Variable | Description | Default |
|---|---|---|
| DEFAULT_TIMEZONE | Default timezone for current_time tool | UTC |
| Environment Variable | Description | Default |
|---|---|---|
| MAX_SLEEP_SECONDS | Maximum allowed sleep duration in seconds | 300 |
The Mem0 Memory Tool supports three different backend configurations:
| 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:
MEM0_API_KEY is set, the tool will use the Mem0 PlatformOPENSEARCH_HOST is set, the tool will use OpenSearchfaiss-cpu package)| 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 |
| 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 |
| Environment Variable | Description | Default |
|---|---|---|
| PYTHON_REPL_BINARY_MAX_LEN | Maximum length for binary content before truncation | 100 |
| Environment Variable | Description | Default |
|---|---|---|
| SHELL_DEFAULT_TIMEOUT | Default timeout in seconds for shell commands | 900 |
| 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 |
| 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 |
| 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 Variable | Description | Default |
|---|---|---|
| ENV_VARS_MASKED_DEFAULT | Default setting for masking sensitive values | true |
| 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 |
| Environment Variable | Description | Default |
|---|---|---|
| STRANDS_DEFAULT_WAIT_TIME | Default setting for wait time with actions | 1 |
| STRANDS_BROWSER_MAX_RETRIES | Default number of retries to perform when an action fails | 3 |
| STRANDS_BROWSER_RETRY_DELAY | Default retry delay time for retry mechanisms | 1 |
| STRANDS_BROWSER_SCREENSHOTS_DIR | Default directory where screenshots will be saved | screenshots |
| STRANDS_BROWSER_USER_DATA_DIR | Default directory where data for reloading a browser instance is stored | ~/.browser_automation |
| STRANDS_BROWSER_HEADLESS | Default headless setting for launching browsers | false |
| STRANDS_BROWSER_WIDTH | Default width of the browser | 1280 |
| STRANDS_BROWSER_HEIGHT | Default height of the browser | 800 |
We welcome contributions! See our Contributing Guide for details on:
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
See CONTRIBUTING for more information.
Strands Agents is currently in public preview. During this period:
strands-agents/tools
May 14, 2025
July 7, 2025
Python