--- title: Publish Custom Tools description: How to build, package, and publish your own CrewAI-compatible tools to PyPI so any CrewAI user can install and use them. icon: box-open mode: "wide" --- ## Overview CrewAI's tool system is designed to be extended. If you've built a tool that could benefit others, you can package it as a standalone Python library, publish it to PyPI, and make it available to any CrewAI user — no PR to the CrewAI repo required. This guide walks through the full process: implementing the tools contract, structuring your package, and publishing to PyPI. If you just need a custom tool for your own project, see the [Create Custom Tools](/en/learn/create-custom-tools) guide instead. ## The Tools Contract Every CrewAI tool must satisfy one of two interfaces: ### Option 1: Subclass `BaseTool` Subclass `crewai.tools.BaseTool` and implement the `_run` method. Define `name`, `description`, and optionally an `args_schema` for input validation. ```python from crewai.tools import BaseTool from pydantic import BaseModel, Field class GeolocateInput(BaseModel): """Input schema for GeolocateTool.""" address: str = Field(..., description="The street address to geolocate.") class GeolocateTool(BaseTool): name: str = "Geolocate" description: str = "Converts a street address into latitude/longitude coordinates." args_schema: type[BaseModel] = GeolocateInput def _run(self, address: str) -> str: # Your implementation here return f"40.7128, -74.0060" ``` ### Option 2: Use the `@tool` Decorator For simpler tools, the `@tool` decorator turns a function into a CrewAI tool. The function **must** have a docstring (used as the tool description) and type annotations. ```python from crewai.tools import tool @tool("Geolocate") def geolocate(address: str) -> str: """Converts a street address into latitude/longitude coordinates.""" return "40.7128, -74.0060" ``` ### Key Requirements Regardless of which approach you use, your tool must: - Have a **`name`** — a short, descriptive identifier. - Have a **`description`** — tells the agent when and how to use the tool. This directly affects how well agents use your tool, so be clear and specific. - Implement **`_run`** (BaseTool) or provide a **function body** (@tool) — the synchronous execution logic. - Use **type annotations** on all parameters and return values. - Return a **string** result (or something that can be meaningfully converted to one). ### Optional: Async Support If your tool performs I/O-bound work, implement `_arun` for async execution: ```python class GeolocateTool(BaseTool): name: str = "Geolocate" description: str = "Converts a street address into latitude/longitude coordinates." def _run(self, address: str) -> str: # Sync implementation ... async def _arun(self, address: str) -> str: # Async implementation ... ``` ### Optional: Input Validation with `args_schema` Define a Pydantic model as your `args_schema` to get automatic input validation and clear error messages. If you don't provide one, CrewAI will infer it from your `_run` method's signature. ```python from pydantic import BaseModel, Field class TranslateInput(BaseModel): """Input schema for TranslateTool.""" text: str = Field(..., description="The text to translate.") target_language: str = Field( default="en", description="ISO 639-1 language code for the target language.", ) ``` Explicit schemas are recommended for published tools — they produce better agent behavior and clearer documentation for your users. ### Optional: Environment Variables If your tool requires API keys or other configuration, declare them with `env_vars` so users know what to set: ```python from crewai.tools import BaseTool, EnvVar class GeolocateTool(BaseTool): name: str = "Geolocate" description: str = "Converts a street address into latitude/longitude coordinates." env_vars: list[EnvVar] = [ EnvVar( name="GEOCODING_API_KEY", description="API key for the geocoding service.", required=True, ), ] def _run(self, address: str) -> str: ... ``` ## Package Structure Structure your project as a standard Python package. Here's a recommended layout: ``` crewai-geolocate/ ├── pyproject.toml ├── LICENSE ├── README.md └── src/ └── crewai_geolocate/ ├── __init__.py └── tools.py ``` ### `pyproject.toml` ```toml [project] name = "crewai-geolocate" version = "0.1.0" description = "A CrewAI tool for geolocating street addresses." requires-python = ">=3.10" dependencies = [ "crewai", ] [build-system] requires = ["hatchling"] build-backend = "hatchling.build" ``` Declare `crewai` as a dependency so users get a compatible version automatically. ### `__init__.py` Re-export your tool classes so users can import them directly: ```python from crewai_geolocate.tools import GeolocateTool __all__ = ["GeolocateTool"] ``` ### Naming Conventions - **Package name**: Use the prefix `crewai-` (e.g., `crewai-geolocate`). This makes your tool discoverable when users search PyPI. - **Module name**: Use underscores (e.g., `crewai_geolocate`). - **Tool class name**: Use PascalCase ending in `Tool` (e.g., `GeolocateTool`). ## Testing Your Tool Before publishing, verify your tool works within a crew: ```python from crewai import Agent, Crew, Task from crewai_geolocate import GeolocateTool agent = Agent( role="Location Analyst", goal="Find coordinates for given addresses.", backstory="An expert in geospatial data.", tools=[GeolocateTool()], ) task = Task( description="Find the coordinates of 1600 Pennsylvania Avenue, Washington, DC.", expected_output="The latitude and longitude of the address.", agent=agent, ) crew = Crew(agents=[agent], tasks=[task]) result = crew.kickoff() print(result) ``` ## Publishing to PyPI Once your tool is tested and ready: ```bash # Build the package uv build # Publish to PyPI uv publish ``` If this is your first time publishing, you'll need a [PyPI account](https://pypi.org/account/register/) and an [API token](https://pypi.org/help/#apitoken). ### After Publishing Users can install your tool with: ```bash pip install crewai-geolocate ``` Or with uv: ```bash uv add crewai-geolocate ``` Then use it in their crews: ```python from crewai_geolocate import GeolocateTool agent = Agent( role="Location Analyst", tools=[GeolocateTool()], # ... ) ```