Zapier MCP costs two tasks a call: batch Sume jobs_wait first
Each Zapier MCP tool call uses two tasks. When an agent uses Sume and Zapier together, wait on all jobs in one jobs_wait, then make one Zapier call.

Zapier states that each MCP tool call uses two tasks from your task quota. If one agent runs Sume generations and then posts each result through Zapier, call Sume's jobs_wait once with up to 20 job_ids, then make one Zapier call for the whole batch instead of one per item. Sume calls do not consume Zapier tasks, since they go to a different server.
| Step | Server | Cost note |
|---|---|---|
| Submit images or clips | Sume MCP | Sume wallet and admission |
| Wait for completion | Sume MCP | No Zapier tasks |
| Post to an app | Zapier MCP | Two tasks per call |
Pattern
Zapier says MCP is included in every plan and draws on the same task bucket as Zaps. Fan-out wastes that bucket, so shape the loop around Sume's batch features.
- Submit the Sume jobs, each with its own
idempotency_key. - Call
jobs_waitwithjob_ids(1 to 20) andwait_for: all. - If
wait_slice_expiredappears, repeat the same wait; do not resubmit. - Read the results with one
jobs_resultbatch call. - Send one combined message through Zapier.
Arithmetic
Twenty finished images posted one by one cost 20 Zapier calls, which is 40 tasks. Posted as one digest, they cost one call, which is 2 tasks. Sume's side is the same either way: one batch wait and one batch read replace 20 waits and 20 reads.
| Approach | Zapier calls | Tasks used | Sume calls after submit |
|---|---|---|---|
| One post per result | 20 | 40 | 20 waits + 20 reads |
| One digest post | 1 | 2 | 1 wait + 1 read |
Caveat
Zapier's page does not say which transport it uses, so check your client's connector for Zapier separately. The Sume side needs only the hosted URL and OAuth or a key.
Checking your own quota
Zapier says its MCP calls draw on the same task bucket as Zaps, so a heavy agent can use up the quota meant for your automations. Look at your plan's task count and divide by two to see how many MCP calls it affords. Then count how many Zapier calls your agent makes per run and see whether batching brings it inside the budget.
Keeping Sume out of the count
The Sume steps are separate. They draw on your Sume wallet and admission limits, not on Zapier tasks. Use a single batch wait and a single batch read, so the agent holds one Sume job set in context and produces one digest for the Zapier step.
Check how failed calls are treated before you design retries. Zapier's page says what counts as a task, and it is worth reading before you build a loop that retries on errors. On the Sume side, a retry of a wait is free of charge, while a retried create needs the same idempotency_key. Keep these two kinds of retry apart in the agent's plan, so an error from one service does not trigger a repeat on the other.
Before you rely on this setup, run a short acceptance test with a read-only credential. Connect, call mcp_health, call tools_list, and read one job with jobs_status. Record the tool count you see, so you can notice later if a credential change alters it. Then repeat the test after any config edit. A five-minute test like this catches most wiring mistakes before they cost money, and it gives you a baseline to compare against when something behaves differently next week.
Sources
More in Integrations
- How to add an MCP server to ChatGPT with developer mode
Turn on ChatGPT developer mode, create an app for the server's URL, and sign in with OAuth. The steps, with Sume's hosted MCP server as the example.
- How to add subtitles to a video in Python
Add subtitles to a video in Python with Requests: POST the video URL to Sume's /v1/video-captions, poll the job, then read the captioned video_url.
- Add Sume to Claude as a custom connector (remote MCP)
Add Sume's hosted MCP server to Claude under Customize > Connectors, see what Sume's OAuth consent grants, and decide whether to allow paid tools.
- Airflow HTTP sensor: wait for an AI video job to finish
Submit an AI video job with Airflow's HttpOperator, then wait with an HttpSensor in reschedule mode that passes once the job's status is completed.
Written by Sume