Google ADK

import asyncio
import os

from google.adk.agents import LlmAgent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.adk.tools.mcp_tool import MCPToolset, StreamableHTTPConnectionParams
from google.genai.types import Content, Part

ZENROWS_API_KEY = os.environ["ZENROWS_API_KEY"]

research_agent = LlmAgent(
    model="gemini-2.5-pro",
    name="research_agent",
    instruction=(
        "You are a thorough web researcher. When given a topic and a starting URL, "
        "visit the URL, identify the 3 most relevant linked articles, scrape each one, "
        "and produce a synthesized report covering key findings, common themes, and "
        "any contradictions. Cite each source with its URL."
    ),
    tools=[
        MCPToolset(
            connection_params=StreamableHTTPConnectionParams(
                url="https://mcp.zenrows.com/mcp",
                headers={
                    "Authorization": f"Bearer {ZENROWS_API_KEY}",
                },
            )
        )
    ],
)


async def main() -> None:
    session_service = InMemorySessionService()
    runner = Runner(
        agent=research_agent,
        app_name="zenrows_research_app",
        session_service=session_service,
    )

    session = await session_service.create_session(
        app_name="zenrows_research_app",
        user_id="user_1",
    )

    prompt = (
        "Research recent developments in AI tools. "
        "Start at https://huggingface.co/blog and follow the most relevant links."
    )
    message = Content(role="user", parts=[Part(text=prompt)])

    async for event in runner.run_async(
        user_id=session.user_id,
        session_id=session.id,
        new_message=message,
    ):
        if event.content and event.content.parts:
            for part in event.content.parts:
                if part.text:
                    print(part.text)


asyncio.run(main())

import os

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool import MCPToolset, StreamableHTTPConnectionParams

ZENROWS_API_KEY = os.environ["ZENROWS_API_KEY"]

zenrows_toolset = MCPToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://mcp.zenrows.com/mcp",
        headers={
            "Authorization": f"Bearer {ZENROWS_API_KEY}",
        },
    )
)

writer_agent = LlmAgent(
    model="gemini-2.5-flash",
    name="writer_agent",
    instruction="Take research findings and produce a polished article.",
)

researcher_agent = LlmAgent(
    model="gemini-2.5-pro",
    name="researcher_agent",
    instruction=(
        "Gather research from the web on the user's topic using ZenRows tools. "
        "Once you have enough material, transfer to the writer_agent for the final draft."
    ),
    tools=[zenrows_toolset],
    sub_agents=[writer_agent],
)