Integrations

Google ADK

Give Google ADK agents tools that run Actors and read their results.

Give agents built with Google's Agent Development Kit Scrape.ly tools: search the Store, run Actors, wait for their runs, and read the results. Agents connect to the hosted MCP server through ADK's McpToolset, so there is no Scrape.ly package to install.

.bash

pip install "google-adk[mcp]"

Create an API token in the dashboard under Settings → API & Integrations and set it as SCRAPELY_TOKEN. The agent can do anything the token can, including starting paid runs, so give it a scoped key: actors:run, runs:read, and datasets:read, with a Max charge per day. See API keys & permissions.

Give an agent Scrape.ly tools

Create a folder for the agent, for example scrapely_agent/, with an empty __init__.py and this agent.py:

.python

import os

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams

root_agent = LlmAgent(
    model="gemini-flash-latest",
    name="web_researcher",
    instruction="Find the right Actor in the Scrape.ly Store, run it, and report what its results show.",
    tools=[
        McpToolset(
            connection_params=StreamableHTTPConnectionParams(
                url="https://mcp.scrape.ly",
                headers={"Authorization": f"Bearer {os.environ['SCRAPELY_TOKEN']}"},
                timeout=30,
                sse_read_timeout=300,
            ),
        )
    ],
)

Run adk web from the folder that contains scrapely_agent/, pick the agent, and ask:

.text

Find an Actor that scrapes Google Maps, run it for 'coffee shops in Berlin' with at most 20 results, and list the name, rating, and address of each place.

adk run scrapely_agent does the same in the terminal. See MCP tools in ADK for more options.

What the agent can do

The agent gets the MCP server's default tools. The ones used most:

Tool	What it does
`search-actors`	Find Actors in the Store by keywords.
`fetch-actor-details`	Read an Actor's input schema, README, and pricing before running it.
`call-actor`	Run an Actor with a JSON input, optionally with `maxItems` and `maxTotalChargeUsd`.
`get-actor-run`	Wait for a run and check its status.
`get-actor-output`	Read a run's results, paged and kept compact.

The full list, including saved inputs and automations, is on the MCP server page. To run one Actor you already know, name it in the prompt, for example Run username/actor-name, so the agent skips the search.

Costs: runs started by the agent are billed like any run. Put the limits in the prompt (such as "at most 20 results"), and keep a Max charge per day on the key.