MCP — The Technology That Makes
Your Business AI-Readable

from aicallable.mcp import MCPServer, tool

server = MCPServer(
    name="my-restaurant",
    version="1.0.0",
    description="Browse menu and place orders"
)

@server.tool(
    description="Check if a menu item is available",
    scopes=["menu:read"]
)
async def check_menu_availability(item_id: str) -> dict:
    item = await db.query(
        "SELECT available FROM menu WHERE id=$1",
        item_id
    )
    return {"item_id": item_id,
            "available": item.available}

@server.tool(
    description="Place an order on behalf of a customer",
    scopes=["orders:write"]
)
async def place_order(
    item_id: str,
    quantity: int,
    delivery_address: str
) -> dict:
    await db.execute(...)
    return {"order_placed": True}

server.deploy()  # AIcallable handles all hosting

from anthropic import Anthropic
from aicallable import MCPClient

# Connect agent to your MCP server
mcp = MCPClient(
    server="my-restaurant",
    api_key="aicall_sk_..."
)

# Tools auto-discovered from manifest
tools = mcp.get_tools()

client = Anthropic()
response = client.messages.create(
    model="claude-opus-4-6",
    tools=tools,
    messages=[{
        "role": "user",
        "content": "Is the pepperoni pizza available "
                  "and order one to 12 Jalan Ampang, KL"
    }]
)
# Agent calls check_menu_availability, then place_order
# Results streamed back via MCP protocol