Workflow & Automation · Integration
Apify
Add Apify to your product for your customers, and give your AI agents governed access to it.
Apify runs scrapers and automations as actors, addressed in the API as username~actor-name with a tilde rather than a slash, which is the first thing that trips people writing URLs by hand. Starting a run with POST /v2/acts/{actorId}/runs returns immediately with a run object in READY or RUNNING state; ?waitForFinish only blocks for up to 60 seconds, so anything longer needs polling of /v2/actor-runs/{runId} or a webhook on run status. Results do not come back in the run response: items land in the run's default dataset and are read from /v2/datasets/{id}/items with offset and limit paging, while single blobs such as OUTPUT or screenshots live in the key-value store. Each account has a memory ceiling, so concurrent runs queue rather than fail loudly, and a run stuck in READY usually means memory is exhausted, not that the actor is broken. fastn keeps each customer's API token, handles the connection upkeep and controls which actors an agent may start.
In your product
Embedded for your customers. Per-tenant auth, no per-customer code, maintained by fastn.
Let a customer connect their own Apify account so runs consume their compute units and their proxy allowance.
Trigger a named actor from inside your product and stream the resulting dataset items into your own tables.
Show run history, status and failure reasons for a customer's scrapers without sending them to the Apify console.
Schedule a recurring actor run per customer and reconcile new dataset items against records you already hold.
For your AI agents
Governed, audited access for the agents you build, through the MCP server.
Let an agent start an approved actor with validated input and return the first page of dataset items, with run starts and compute spend audited per tenant.
Have an agent poll a long-running run and summarise why it aborted when it fails.
Allow an agent to read datasets and key-value store records but not to abort or delete other users' runs.
Example prompt
Run our LinkedIn company scraper on this list of domains and show me what came back.
Set up Apify in 4 steps
- 01Enable the Apify connector from your fastn dashboard.
- 02Have each customer authorise their own Apify account, so calls run under their credentials rather than a shared key.
- 03Decide which processes, runs and queues your product needs, map those fields, then enable the actions and triggers you want.
- 04Call it from your product and expose it to your agents through the same governed connection.
Why teams use the Apify integration
What you get by embedding it with fastn instead of building it yourself.
- Ship an Apify integration without building it. Your customers connect their own Apify account inside your product and work their processes, runs and queues there, with no per-customer code on your side.
- Handle the part that actually costs time: runs are asynchronous and can fail long after they are accepted, so an outcome that never arrives must look different from one that succeeded. fastn owns the auth, token refresh, rate limits, pagination and breaking-change fixes, so an Apify update is not your on-call problem.
- One integration serves your product and your agents. The same governed Apify connection powers in-product features and gives AI agents scoped, audited access, so you start work in the automation platform your customers already run, and get the outcome back without wiring it twice.
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PostmarkApify integration FAQ
How do I add an Apify integration to my product?
Enable the Apify connector in your fastn dashboard, then let each customer authenticate their own Apify account. fastn handles the OAuth flow, token storage and refresh per tenant, so there is no Apify client code in your app and no per-customer branch in your codebase. Setup is 4 steps.
Do my customers each connect their own Apify account?
Yes. Every connection is scoped to the individual customer, so each authorises their own Apify account and only ever sees their own processes, runs and queues. That per-tenant isolation is the point of an embedded integration: you support the long tail of customer setups without maintaining an integration per customer.
Can AI agents use this Apify integration?
Yes. The same connection is exposed to your agents through the fastn MCP gateway, with permissions scoped per tenant and every call audited. Let an agent start an approved actor with validated input and return the first page of dataset items, with run starts and compute spend audited per tenant.
Who maintains the Apify integration?
fastn does. When Apify changes an endpoint, deprecates a field or alters its auth, the fix lands in the connector rather than in your backlog, and your customers' connections keep working.
Can my product start an Apify run and read its outcome?
Yes. Your product can trigger a process in the customer's own Apify account, pass it input, and take the result back as an event rather than polling for it.
What happens when an Apify run is slow or fails?
The failure surfaces with its error rather than as a silent timeout, and the run keeps its own identifier so a retry can be matched to the original. That matters more here than in most integrations, because a run that half-completed is not the same as one that never started.
What can I build with the Apify integration?
A common starting point: let a customer connect their own Apify account so runs consume their compute units and their proxy allowance. Teams also use it for the other use cases listed above, and expose it to agents for governed reads and writes.
How much does the Apify integration cost?
It is included. Pricing is based on connected accounts, not on how many connectors you enable, so adding Apify does not change your per-connector cost. You can start free with 3 connected accounts.
Add Apify to your product
Start free with 3 connected accounts. No sales call required, and no per-customer integration code.