Google ADK

pip install google-adk python-dotenv

import asyncio
import os
from pathlib import Path

from dotenv import load_dotenv
from google.adk.agents import LlmAgent
from google.adk.runners import InMemoryRunner
from google.adk.tools.mcp_tool import McpToolset, StreamableHTTPConnectionParams
from google.genai import types


async def main():
    load_dotenv()

    twexapi_toolset = McpToolset(
        connection_params=StreamableHTTPConnectionParams(
            url="https://api.twexapi.io/mcp",
            headers={"x-api-key": os.environ["TWEXAPI_API_KEY"]},
        )
    )

    agent = LlmAgent(
        model="gemini-2.5-flash",
        name="twexapi_agent",
        instruction=(
            "You help users interact with X/Twitter through Twexapi MCP. "
            "Call explore first. Preserve tweet IDs, user IDs, cursors, and route_used."
        ),
        tools=[twexapi_toolset],
    )

    runner = InMemoryRunner(agent=agent, app_name="twexapi_app")
    session = await runner.session_service.create_session(
        app_name="twexapi_app",
        user_id="user-1",
    )

    response_parts = []
    async for event in runner.run_async(
        user_id="user-1",
        session_id=session.id,
        new_message=types.Content(
            role="user",
            parts=[
                types.Part(
                    text=(
                        "Fetch trending tweets for united-states with topic technology "
                        "and content AI. Return tweet IDs, authors, engagement metrics, "
                        "has_more, and next_cursor."
                    )
                )
            ],
        ),
    ):
        if event.content and event.content.parts:
            response_parts.extend(part.text for part in event.content.parts if part.text)

    Path("twexapi-adk-handoff.json").write_text(
        "".join(response_parts),
        encoding="utf-8",
    )

    await twexapi_toolset.close()


asyncio.run(main())

researcher = LlmAgent(
    model="gemini-2.5-flash",
    name="researcher",
    instruction="Collect X/Twitter data through Twexapi MCP and return compact JSON.",
    tools=[twexapi_toolset],
)

analyst = LlmAgent(
    model="gemini-2.5-flash",
    name="analyst",
    instruction="Analyze structured tweet rows. Do not call external tools.",
)

from google.adk.tools.mcp_tool import McpToolset, StreamableHTTPConnectionParams


def get_headers(context):
    return {"x-api-key": context.state["twexapi_api_key"]}


twexapi_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://api.twexapi.io/mcp",
    ),
    header_provider=get_headers,
)

planning_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://api.twexapi.io/mcp",
        headers={"x-api-key": os.environ["TWEXAPI_API_KEY"]},
    ),
    tool_filter=["explore"],
)