arcade-mcp/libs/arcade-mcp-server/docs/examples/01_tools.md

01 - Tools

Learn how to create tools with different parameter types and how arcade_mcp_server discovers them automatically.

Running the Example

• Run: python -m arcade_mcp_server
• Run (stdio): python -m arcade_mcp_server stdio
• Show loaded packages: python -m arcade_mcp_server --show-packages
• Load specific package: python -m arcade_mcp_server --tool-package github
• Discover all installed: python -m arcade_mcp_server --discover-installed

Source Code

--8<-- "docs/examples/01_tools.py"

Creating Tools

1. Simple Tools

Basic tools with simple parameter types:

@tool
def hello(name: Annotated[str, "Name to greet"]) -> str:
    """Say hello to someone."""
    return f"Hello, {name}!"

@tool
def add(
    a: Annotated[float, "First number"],
    b: Annotated[float, "Second number"]
) -> Annotated[float, "Sum of the numbers"]:
    """Add two numbers together."""
    return a + b

2. List Parameters

Working with lists of values:

@tool
def calculate_average(
    numbers: Annotated[list[float], "List of numbers to average"]
) -> Annotated[float, "Average of all numbers"]:
    """Calculate the average of a list of numbers."""
    if not numbers:
        return 0.0
    return sum(numbers) / len(numbers)

3. Complex Types with TypedDict

Using TypedDict for structured input and output:

class PersonInfo(TypedDict):
    name: str
    age: int
    email: str
    is_active: bool

@tool
def create_user_profile(
    person: Annotated[PersonInfo, "Person's information"]
) -> Annotated[str, "Formatted user profile"]:
    """Create a formatted user profile from person information."""
    # Implementation here

Tool Discovery

The arcade_mcp_server CLI discovers tools in multiple ways:

1. Current Directory

• Scans all *.py files in the current directory
• Imports and checks for @tool decorated functions

2. Standard Directories

• tools/ directory - Common convention for organizing tools
• arcade_tools/ directory - Alternative naming convention
• Both are recursively scanned for Python files

3. Package Loading

# Load a specific package
python -m arcade_mcp_server --tool-package github

# Discover all installed arcade packages
python -m arcade_mcp_server --discover-installed

4. File Organization

Example project structure:

my_project/
├── hello.py          # Contains @tool functions
├── tools/
│   └── math.py      # More @tool functions
└── arcade_tools/
    └── utils.py     # Even more @tool functions

Best Practices

Parameter Annotations

• Always use Annotated: Provide descriptions for all parameters
• Clear descriptions: Help the AI understand what each parameter does
• Type hints: Use proper Python type hints for validation

Tool Design

• Single purpose: Each tool should do one thing well
• Error handling: Add validation and helpful error messages
• Return types: Always annotate return types with descriptions

Organization

• Group related tools: Use directories to organize by functionality
• Naming conventions: Use clear, descriptive names
• Documentation: Write clear docstrings for each tool

Key Concepts

• Auto-Discovery: Automatically finds tools without explicit registration
• Type Safety: Full type annotation support with runtime validation
• TypedDict Support: Use TypedDict for complex structured data
• Flexible Organization: Structure your tools however makes sense for your project
• Multiple Sources: Discover from files, directories, and packages