Integrations

Amazon Bedrock

Give Bedrock agents built with Strands Scrape.ly tools.

Give agents running on Amazon Bedrock models Scrape.ly tools: search the Store, run Actors, wait for their runs, and read the results. Agents built with Strands Agents, AWS's open-source agent SDK, connect to the hosted MCP server, so there is no Scrape.ly package to install.

.bash

pip install strands-agents

The agent calls Bedrock with your AWS credentials, so set them up as for any Bedrock app and enable the model in your account. 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

Open the server with Strands' MCPClient and pass its tools to the agent.

.python

import os

from strands import Agent
from strands.tools.mcp import MCPClient

scrapely = MCPClient(
    url="https://mcp.scrape.ly",
    headers={"Authorization": f"Bearer {os.environ['SCRAPELY_TOKEN']}"},
)

with scrapely:
    agent = Agent(
        system_prompt="Find the right Actor in the Scrape.ly Store, run it, and report what its results show.",
        tools=scrapely.list_tools_sync(),
    )
    agent(
        "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."
    )

Strands uses its default Bedrock model unless you pass one with model=BedrockModel(model_id=...). See MCP in Strands for more options.

Bedrock AgentCore Gateway

To share Scrape.ly with agents through an AgentCore Gateway, add the hosted server as an MCP server target with OAuth outbound auth. The gateway signs in through the server's OAuth flow, so there is no token to copy.

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.