MCP + API + CLI PRODUCT DATA FOR AI AGENTS

You    I need a 4 person camping tent from a UK shop. Show a few options with prices.
Agent  search_products {"query":"4 person camping tent","country":"GB"}
       → Eurohike Sendero 4 Family Tent · £100.00 · Amazon.co.uk
       → Pro Action 4 Person 1 Room Tunnel Camping Tent · £80.00 · Argos
       → Halfords 4 Person Vis A Vis Tent XL · £50.00 · Halfords
       → Decathlon 4 Man Tent · £119.99 · Decathlon UK
       (retrieved 23 Oct 2026)

# pip install mcp
import asyncio, os
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

async def main():
    headers = {"Authorization": f"Bearer {os.environ['DATAWEBOT_API_KEY']}"}
    async with streamablehttp_client("https://mcp.datawebot.com/mcp", headers=headers) as (read, write, _):
        async with ClientSession(read, write) as session:
            await session.initialize()
            result = await session.call_tool("search_products", {"query":"4 person camping tent","country":"GB"})
            print(result.content[0].text)

asyncio.run(main())

curl https://api.datawebot.com/v1/jobs \
  -H "Authorization: Bearer $DATAWEBOT_API_KEY" \
  -H "Idempotency-Key: amazon-coffee-0001" \
  -H "Content-Type: application/json" \
  -d '{"blueprint_id":"amazon.search_items","url":"https://www.amazon.com/s?k=coffee","parameters":{"max_pages":1}}'

# Then poll GET /v1/jobs/{job_id} until it finishes,
# and read GET /v1/jobs/{job_id}/results, following next_cursor.