A client asked a question that sounds simple: which sellers on the marketplaces are risky to buy from? Answering it takes two steps. Find the sellers behind the product listings, then check each seller's legal entity against public risk registries.
I had an Actor for each half already. One walks marketplace search results and returns sellers with their tax ID, legal name and store URL. The other takes tax IDs and returns a risk score built from bankruptcy filings, tax arrears, the procurement blacklist and the financial monitoring list. Both had been in the Store for months, both had paying users.
The first Actor, doing its half of the job. Each of these runs produces the input for the second one.
Handing the chain to an agent broke it three times, and none of the breaks looked like a failure. The runs stayed green. The dataset filled up. The answer was wrong in a way that only showed up when I checked a company by hand.
The agent reached both Actors through the Apify MCP server, which exposes them as tools over the Model Context Protocol. Nothing below depends on which client you use: the failures come from how the two Actors hand data to each other, and a human doing the same handoff by hand would have hit two of the three.
