---
source_url: "https://docs.crewai.com/v1.15.1/en/concepts/tools"
title: Tools - CrewAI
mirrored_at: 2026-08-06T01:10:48.020Z
host: docs.crewai.com
cited_in_42a: true
mirror_canonical: "https://index.42a.ai/docs.crewai.com/v1.15.1/en/concepts/tools"
---

> **Original source:** https://docs.crewai.com/v1.15.1/en/concepts/tools

## Overview

CrewAI tools empower agents with capabilities ranging from web searching and data analysis to collaboration and delegating tasks among coworkers. This documentation outlines how to create, integrate, and leverage these tools within the CrewAI framework, including a new focus on collaboration tools.

## What is a Tool?

A tool in CrewAI is a skill or function that agents can utilize to perform various actions. This includes tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools), enabling everything from simple searches to complex interactions and effective teamwork among agents.

## Key Characteristics of Tools

-   **Utility**: Crafted for tasks such as web searching, data analysis, content generation, and agent collaboration.
-   **Integration**: Boosts agent capabilities by seamlessly integrating tools into their workflow.
-   **Customizability**: Provides the flexibility to develop custom tools or utilize existing ones, catering to the specific needs of agents.
-   **Error Handling**: Incorporates robust error handling mechanisms to ensure smooth operation.
-   **Caching Mechanism**: Features intelligent caching to optimize performance and reduce redundant operations.
-   **Asynchronous Support**: Handles both synchronous and asynchronous tools, enabling non-blocking operations.
-   **Typed Outputs**: Uses optional Pydantic models to give agents clear JSON fields while direct Python calls still receive the tool’s normal return value.

## Using CrewAI Tools

To enhance your agents’ capabilities with crewAI tools, begin by installing our extra tools package:

Here’s an example demonstrating their use:

Code

## Available CrewAI Tools

-   **Error Handling**: All tools are built with error handling capabilities, allowing agents to gracefully manage exceptions and continue their tasks.
-   **Caching Mechanism**: All tools support caching, enabling agents to efficiently reuse previously obtained results, reducing the load on external resources and speeding up the execution time. You can also define finer control over the caching mechanism using the `cache_function` attribute on the tool.

Here is a list of the available tools and their descriptions:

Tool

Description

**ApifyActorsTool**

A tool that integrates Apify Actors with your workflows for web scraping and automation tasks.

**BrowserbaseLoadTool**

A tool for interacting with and extracting data from web browsers.

**CodeDocsSearchTool**

A RAG tool optimized for searching through code documentation and related technical documents.

**CodeInterpreterTool**

A tool for interpreting python code.

**ComposioTool**

Enables use of Composio tools.

**CSVSearchTool**

A RAG tool designed for searching within CSV files, tailored to handle structured data.

**DALL-E Tool**

A tool for generating images using the DALL-E API.

**DirectorySearchTool**

A RAG tool for searching within directories, useful for navigating through file systems.

**DOCXSearchTool**

A RAG tool aimed at searching within DOCX documents, ideal for processing Word files.

**DirectoryReadTool**

Facilitates reading and processing of directory structures and their contents.

**ExaSearchTool**

Search the web with Exa, the fastest and most accurate web search API. Supports token-efficient highlights and full page content.

**FileReadTool**

Enables reading and extracting data from files, supporting various file formats.

**FirecrawlSearchTool**

A tool to search webpages using Firecrawl and return the results.

**FirecrawlCrawlWebsiteTool**

A tool for crawling webpages using Firecrawl.

**FirecrawlScrapeWebsiteTool**

A tool for scraping webpages URL using Firecrawl and returning its contents.

**GithubSearchTool**

A RAG tool for searching within GitHub repositories, useful for code and documentation search.

**SerperDevTool**

A specialized tool for development purposes, with specific functionalities under development.

**TXTSearchTool**

A RAG tool focused on searching within text (.txt) files, suitable for unstructured data.

**JSONSearchTool**

A RAG tool designed for searching within JSON files, catering to structured data handling.

**LlamaIndexTool**

Enables the use of LlamaIndex tools.

**MDXSearchTool**

A RAG tool tailored for searching within Markdown (MDX) files, useful for documentation.

**PDFSearchTool**

A RAG tool aimed at searching within PDF documents, ideal for processing scanned documents.

**PGSearchTool**

A RAG tool optimized for searching within PostgreSQL databases, suitable for database queries.

**Vision Tool**

A tool for generating images using the DALL-E API.

**RagTool**

A general-purpose RAG tool capable of handling various data sources and types.

**ScrapeElementFromWebsiteTool**

Enables scraping specific elements from websites, useful for targeted data extraction.

**ScrapeWebsiteTool**

Facilitates scraping entire websites, ideal for comprehensive data collection.

**WebsiteSearchTool**

A RAG tool for searching website content, optimized for web data extraction.

**XMLSearchTool**

A RAG tool designed for searching within XML files, suitable for structured data formats.

**YoutubeChannelSearchTool**

A RAG tool for searching within YouTube channels, useful for video content analysis.

**YoutubeVideoSearchTool**

A RAG tool aimed at searching within YouTube videos, ideal for video data extraction.

## Creating your own Tools

There are two main ways for one to create a CrewAI tool:

### Subclassing `BaseTool`

Code

### Typed Tool Outputs

When a tool returns structured data, define a Pydantic output model. This gives the agent field names it can trust, such as `sku`, `quantity`, or `needs_reorder`. Direct Python calls still receive the value your tool returns. When an agent uses the tool, CrewAI sends the agent a JSON string based on the output model.

Code

To send Markdown or another short text format to the agent, override `format_output_for_agent`. Direct calls to `tool.run(...)` still return the normal Python value.

Code

If you do not override `format_output_for_agent`, typed outputs are sent to the agent as JSON. Plain string results work as before.

## Asynchronous Tool Support

CrewAI supports asynchronous tools, allowing you to implement tools that perform non-blocking operations like network requests, file I/O, or other async operations without blocking the main execution thread.

### Creating Async Tools

You can create async tools in two ways:

#### 1\. Using the `tool` Decorator with Async Functions

Code

#### 2\. Implementing Async Methods in Custom Tool Classes

Code

### Using Async Tools

Async tools work seamlessly in both standard Crew workflows and Flow-based workflows:

Code

The CrewAI framework automatically handles the execution of both synchronous and asynchronous tools, so you don’t need to worry about how to call them differently.

### Utilizing the `tool` Decorator

Code

### Custom Caching Mechanism

Code

## Conclusion

Tools are pivotal in extending the capabilities of CrewAI agents, enabling them to undertake a broad spectrum of tasks and collaborate effectively. When building solutions with CrewAI, leverage both custom and existing tools to empower your agents and enhance the AI ecosystem. Consider utilizing error handling, caching mechanisms, and the flexibility of tool arguments to optimize your agents’ performance and capabilities.