AgenticX Tool Creator

Guide for building tools that extend agent capabilities.

Tool Architecture

AgenticX tools inherit from BaseTool and are consumed by agents during execution. Three approaches exist:

1. Function decorator (@tool), fastest for simple tools
2. Class-based (extend BaseTool), for complex or stateful tools
3. MCP remote tools, for external services via Model Context Protocol

Function Decorator Tools

from agenticx.tools import tool

@tool
def search_web(query: str) -> str:
    """Search the web for information.

    Args:
        query: The search query string.

    Returns:
        Search results as text.
    """
    # implementation
    return f"Results for: {query}"

@tool
def read_file(path: str) -> str:
    """Read contents of a local file."""
    with open(path) as f:
        return f.read()

The @tool decorator reads the function signature and docstring to generate the tool schema automatically. The docstring is the tool description the LLM sees.

Class-Based Tools

For tools needing initialization, state, or complex logic:

from agenticx.core import BaseTool

class DatabaseQuery(BaseTool):
    name = "database_query"
    description = "Query the project database."

    def __init__(self, connection_string: str):
        super().__init__()
        self.conn = connect(connection_string)

    def _run(self, sql: str) -> str:
        return self.conn.execute(sql).fetchall()

Tool Registry

Register and discover tools globally:

from agenticx.core import ToolRegistry

registry = ToolRegistry()
registry.register(search_web)
registry.register(read_file)

# List all registered tools
for t in registry.list_tools():
    print(f"{t.name}: {t.description}")

MCP Integration

AgenticX supports the Model Context Protocol for remote tool access.

Connecting to an MCP Server

from agenticx.protocols import MCPClient