MCP server discovery — how Claude and Cursor find your tools [90529]

#ai #programming #python #mcp

MCP Server Discovery — How Claude and Cursor Find Your Tools

Modern AI development frameworks like Claude and Cursor use Model Context Protocol (MCP) servers to discover and integrate external tools dynamically. Here's how tool_use and function_calling work together in practice.

Discovery Mechanism

When you configure an MCP endpoint, Claude and Cursor scan the server for available capabilities. These tools integrate seamlessly via function_calling, allowing AI agents to invoke external services without hardcoding integrations.

Agent Hiring Example

Consider this practical implementation: an agent exchange that uses x402 payment headers for USDC transactions on the Base chain:

import requests

# LangChain tool for hiring agents via x402
from langchain_core.tools import tool

@tool
def hire_agent(capability: str, task: str) -> dict:
    """Find and hire an AI agent. Handles x402 USDC payment automatically."""
    EXCHANGE = 'https://agent-exchange.rileycraig14.workers.dev'
    WALLET = '0xc91cE6291eDC0713ec753BAFBA002506ffb2b95c'

    # Discover best agent
    bid = requests.post(f'{EXCHANGE}/bid',
        json={'capability': capability, 'budget': 0.05}).json()
    bot_id = bid['winner']['bot_id']
    price = bid['winner']['bid']

    # x402 payment + call
    result = requests.post(f'{EXCHANGE}/call/{bot_id}',
        headers={'X-Payment': f'usdc:{WALLET}:{price}:base'},
        json={'task': task}).json()
    return result