Andrew Adams · Co-Founder & Operations at Wireflow · AI Workflow API
Every workflow you build on Wireflow becomes a REST endpoint.
Send one authenticated POST and the whole node graph runs in order, from a Claude Sonnet 4.5 brief step to Nano Banana Lite renders, then poll for the outputs. No SDK, no servers to manage.
Free to build · no credit card
One endpoint runs the whole pipeline
Traditional AI integrations mean a separate API call per model, custom glue code, and per-model error handling. Wireflow collapses that into one request. You POST to a workflow's execute URL with a Bearer token, get an executionId back immediately, and poll the execution endpoint until the state moves from RUNNING to COMPLETED. Each node passes its output downstream automatically, so the graph runs itself.
The flow published on this page is real, not a mockup. Inside it, a Claude Sonnet 4.5 step expands a short product brief into detailed image direction, then two Nano Banana Lite nodes render a studio shot and a restaged lifestyle scene. You design that graph in the visual AI workflow builder and call it as an endpoint without changing a line.
API capabilities
One POST executes
Run the whole workflow with a single authenticated POST and get an executionId back at once.
Poll for results
Poll the execution endpoint with backoff until the run reports COMPLETED, then read node outputs.
Bearer token auth
Generate an sk- key and authenticate every request with one Authorization header, no OAuth.
Webhook triggers
Expose a per-workflow webhook URL so Zapier, CI, or a form can fire a run with no API key.
Idempotent retries
Send an Idempotency-Key so a repeated POST replays the first response instead of rerunning.
Node-level logs
Each execution returns per-node timing and credit cost so you can trace exactly what ran.
Callable by code and by agents
Because a workflow is defined as a graph, the same published flow is exposed two ways: as a REST endpoint for your code and as a hosted MCP tool for agents. An agent can list the workflow, read its typed inputs, run it, and receive the asset URLs back, which is the pattern behind Wireflow's MCP server. Your scripts hit the same endpoint with plain HTTP.
The async execute-and-poll shape is what makes long jobs safe. The call returns straight away with an executionId, so nothing holds a connection open while models run. Combine that with the no-auth webhook trigger and an Idempotency-Key header, and you have reliable batch AI pipeline automation that survives network retries.
What the API is not
Wireflow is the execution layer, not a strategy brain. The API runs the graph you designed and returns assets, but the brief, the model choices, and the final judgment stay with you or the agent you bring. It is a hosted platform, so there is no offline mode and nothing to self-host: if you specifically want to run nodes on your own machine, a local tool like the ComfyUI alternative comparison covers that tradeoff.
It is also not a magic scaler. Every node costs credits, and a run that exceeds your balance returns a clear error showing which nodes cost what, rather than failing halfway. For high daily volume and higher rate limits, the enterprise plan lifts the ceilings.
More Than Just AI Workflow API
One call runs the chain
One authenticated POST runs the whole graph in order. This flow chains a brief step with two renders, real AI model chaining.
No SDK, just REST
The API is plain REST and JSON, so curl or fetch is enough. Prototype the graph first in AI creative workflows, then call it.
Async, no waiting
Execute returns an executionId at once and you poll for results, so long runs never hold a connection, ideal for an AI video workflow.
Webhooks trigger runs
Each workflow exposes a no-auth webhook, so Zapier, CI, or a form can fire it. Pair it with reusable AI templates for repeat jobs.
Agents can call it too
The same endpoint is exposed as an MCP tool, so an agent can list the workflow, run it, and read the returned asset URLs.
Workflow api Workflows
No Code Required
API & Batch Processing
FAQs
It is a REST endpoint that runs a multi-step AI pipeline. You POST once to a workflow's execute URL, get an executionId back, and poll the execution endpoint until every node finishes.
More From Wireflow
Written by
Andrew Adams · Co-Founder & Operations at Wireflow
Runs client operations and content strategy at Wireflow. Works directly with creative teams and agencies to build production AI workflows.
Read the API docs and call your first workflow
Every workflow on Wireflow ships as a REST endpoint and an MCP tool. Read the API overview to see how to authenticate, execute a flow, and poll for outputs, then open the live flow on this page.