crewAI-tools
Extend the capabilities of your CrewAI agents with Tools
Stars: 1255
This repository provides a guide for setting up tools for crewAI agents to enhance functionality. It offers steps to equip agents with ready-to-use tools and create custom ones. Tools are expected to return strings for generating responses. Users can create tools by subclassing BaseTool or using the tool decorator. Contributions are welcome to enrich the toolset, and guidelines are provided for contributing. The development setup includes installing dependencies, activating virtual environment, setting up pre-commit hooks, running tests, static type checking, packaging, and local installation. The goal is to empower AI solutions through advanced tooling.
README:
Empower your CrewAI agents with powerful, customizable tools to elevate their capabilities and tackle sophisticated, real-world tasks.
CrewAI Tools provide the essential functionality to extend your agents, helping you rapidly enhance your automations with reliable, ready-to-use tools or custom-built solutions tailored precisely to your needs.
Homepage | Documentation | Examples | Community
CrewAI provides an extensive collection of powerful tools ready to enhance your agents:
-
File Management:
FileReadTool,FileWriteTool -
Web Scraping:
ScrapeWebsiteTool,SeleniumScrapingTool -
Database Integrations:
PGSearchTool,MySQLSearchTool -
Vector Database Integrations:
MongoDBVectorSearchTool,QdrantVectorSearchTool,WeaviateVectorSearchTool -
API Integrations:
SerperApiTool,EXASearchTool -
AI-powered Tools:
DallETool,VisionTool,StagehandTool
And many more robust tools to simplify your agent integrations.
CrewAI offers two straightforward approaches to creating custom tools:
Define your tool by subclassing:
from crewai.tools import BaseTool
class MyCustomTool(BaseTool):
name: str = "Tool Name"
description: str = "Detailed description here."
def _run(self, *args, **kwargs):
# Your tool logic hereQuickly create lightweight tools using decorators:
from crewai import tool
@tool("Tool Name")
def my_custom_function(input):
# Tool logic here
return outputCrewAI Tools supports the Model Context Protocol (MCP). It gives you access to thousands of tools from the hundreds of MCP servers out there built by the community.
Before you start using MCP with CrewAI tools, you need to install the mcp extra dependencies:
pip install crewai-tools[mcp]
# or
uv add crewai-tools --extra mcpTo quickly get started with MCP in CrewAI you have 2 options:
In this scenario we use a contextmanager (with statement) to start and stop the the connection with the MCP server.
This is done in the background and you only get to interact with the CrewAI tools corresponding to the MCP server's tools.
For an STDIO based MCP server:
from mcp import StdioServerParameters
from crewai_tools import MCPServerAdapter
serverparams = StdioServerParameters(
command="uvx",
args=["--quiet", "[email protected]"],
env={"UV_PYTHON": "3.12", **os.environ},
)
with MCPServerAdapter(serverparams) as tools:
# tools is now a list of CrewAI Tools matching 1:1 with the MCP server's tools
agent = Agent(..., tools=tools)
task = Task(...)
crew = Crew(..., agents=[agent], tasks=[task])
crew.kickoff(...)For an SSE based MCP server:
serverparams = {"url": "http://localhost:8000/sse"}
with MCPServerAdapter(serverparams) as tools:
# tools is now a list of CrewAI Tools matching 1:1 with the MCP server's tools
agent = Agent(..., tools=tools)
task = Task(...)
crew = Crew(..., agents=[agent], tasks=[task])
crew.kickoff(...)If you need more control over the MCP connection, you can instanciate the MCPServerAdapter into an mcp_server_adapter object which can be used to manage the connection with the MCP server and access the available tools.
important: in this case you need to call mcp_server_adapter.stop() to make sure the connection is correctly stopped. We recommend that you use a try ... finally block run to make sure the .stop() is called even in case of errors.
Here is the same example for an STDIO MCP Server:
from mcp import StdioServerParameters
from crewai_tools import MCPServerAdapter
serverparams = StdioServerParameters(
command="uvx",
args=["--quiet", "[email protected]"],
env={"UV_PYTHON": "3.12", **os.environ},
)
try:
mcp_server_adapter = MCPServerAdapter(serverparams)
tools = mcp_server_adapter.tools
# tools is now a list of CrewAI Tools matching 1:1 with the MCP server's tools
agent = Agent(..., tools=tools)
task = Task(...)
crew = Crew(..., agents=[agent], tasks=[task])
crew.kickoff(...)
# ** important ** don't forget to stop the connection
finally:
mcp_server_adapter.stop()And finally the same thing but for an SSE MCP Server:
from mcp import StdioServerParameters
from crewai_tools import MCPServerAdapter
serverparams = {"url": "http://localhost:8000/sse"}
try:
mcp_server_adapter = MCPServerAdapter(serverparams)
tools = mcp_server_adapter.tools
# tools is now a list of CrewAI Tools matching 1:1 with the MCP server's tools
agent = Agent(..., tools=tools)
task = Task(...)
crew = Crew(..., agents=[agent], tasks=[task])
crew.kickoff(...)
# ** important ** don't forget to stop the connection
finally:
mcp_server_adapter.stop()Always make sure that you trust the MCP Server before using it. Using an STDIO server will execute code on your machine. Using SSE is still not a silver bullet with many injection possible into your application from a malicious MCP server.
- At this time we only support tools from MCP Server not other type of primitives like prompts, resources...
- We only return the first text output returned by the MCP Server tool using
.content[0].text
- Simplicity & Flexibility: Easy-to-use yet powerful enough for complex workflows.
- Rapid Integration: Seamlessly incorporate external services, APIs, and databases.
- Enterprise Ready: Built for stability, performance, and consistent results.
We welcome contributions from the community!
- Fork and clone the repository.
- Create a new branch (
git checkout -b feature/my-feature). - Commit your changes (
git commit -m 'Add my feature'). - Push your branch (
git push origin feature/my-feature). - Open a pull request.
pip install crewai[tools]- Install dependencies:
uv sync - Run tests:
uv run pytest - Run static type checking:
uv run pyright - Set up pre-commit hooks:
pre-commit install
Join our rapidly growing community and receive real-time support:
Build smarter, faster, and more powerful AI solutions—powered by CrewAI Tools.
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