How I chained three Apify Actors into a source-safe MCP agent
After making one business-registry Actor usable through the Apify MCP server, I tried the next obvious step: give an agent several company-research tools at once. My test question sounded harmless: “What evidence can you find about Goldman Sachs as a New York entity, public filer, and website?” The first version of my workflow tried to flatten every result into one company object. That broke the…
The author describes chaining three Apify Actors into a single source-safe MCP (Managed Control Plane) agent to conduct a comprehensive search on Goldman Sachs. The three Actors employed are the US Business Entity Search for state registry evidence, the Domain Availability Checker and WHOIS Scraper for authoritative RDAP, DNS, and domain-age evidence, and the SEC EDGAR Company Filings for the public filer, Central Index Key (CIK), ticker, and filing links.
The workflow taken by the agent does not ask any of these Actors to infer a public ticker, identify a legal entity, or treat an SEC filing as a state good-standing record. Instead, the final output presents a source-separated evidence bundle, explicitly stating that the three sources describe different records and that name, ticker, and domain similarity do not establish a single legal entity.
The article details how the Apify MCP server accepts a comma-separated list of tools, specifying the three chosen Actors. It also explains the importance of verifying the hosted MCP names against the local Actor names to prevent errors. The script runs each Actor, then reads the default dataset, ensuring that the three sources are handled separately, with a warning included in the data contract to remind the user that the sources describe different records.
Key technical aspects include the use of Python 3.10 or newer, the requests package, and setting an API token as an environment variable for security. The actors are used with pay-per-event pricing, amounting to a total charge of $0.0063 for the test run.
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