Developer Tools
Build an API testing and debugging tool
Kliv is an AI app builder. Describe the API testing and debugging tool your team needs — saved requests, scheduled probes, response diffs, incidents, and partner walls — and it builds it.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t a desktop API client or a shared collection service — it’s an AI that builds software for you.
You describe the app you need in plain words, and Kliv builds the database, the logic, the screens, scheduled jobs, and access rules. You own the result and can change it later by asking for changes. It isn’t a template workspace.
On this page, that app is an API testing and debugging workbench. Kliv builds all kinds of web apps; this one helps a team remember requests, run probes, compare responses, and keep incidents tied to evidence.
Why shared request collections stop scaling
An API client on each laptop can work for one integration and two engineers. It stops working when there are many partner APIs, teammates in different time zones, and customers asking whether the outage came from your code or a partner change.
Kliv builds the workbench as a system of record. Every endpoint, saved request, probe result, response diff, and incident is a row in a shared database, with permissions and history that survive beyond one person’s laptop.
The furniture of a request
Five records turn a saved request into a debugging workflow.
Endpoint records
Base URLs per environment, auth style, partner contact, and the changelog you maintain. Requests and incidents hang from this record.
Saved requests
Headers, body, and assertions such as expected status, expected shape, and latency ceiling. A request becomes a test when it has assertions.
Probe schedules
Server-side functions replay saved requests on a schedule, such as every fifteen minutes against staging and hourly against production. A failed assertion opens an incident.
Incidents
An incident keeps the response diff, timeline, affected merchants, and who was told when.
Partner walls
Engineers see the partners assigned to them. A client status view shows its own integrations and nothing past them.
An example: Priya’s shipping integration team
Here’s how one team might use an API testing workbench built with Kliv. It’s only an example — you would describe your own partners, requests, environments, assertions, and incident rules.
A partner changes a response without warning
A carrier deploys to staging and the version header changes from 2.13 to 2.14. There is no email and no changelog entry from the carrier.
The scheduled probe catches the shape change
Priya’s probe finds that the tracking payload gained one field and lost another. The endpoint still returns 200, but the shape assertion fails.
The incident opens with the diff attached
The affected merchants are named from the data because only two route freight through this carrier. Severity does not depend on guesswork.
The team replays staging and production side by side
On Monday, the saved request runs against both environments in one view. The change is scoped, the fix is a mapping update, and the investigation stays on one screen.
The client reads a scoped timeline
The merchant sees its own incident page: what changed, when the team knew, and what was done. Other merchants’ integrations are not visible.
Describe the API workbench you want
Kliv builds from your description, so include partners, environments, schedules, assertions, incident rules, and who can see what. The more detail you give, the closer the first version.
Carrier API workbench
Saved requests, probes, and incidents for shipping partners.
“Build an API testing workbench for our shipping integrations. Save requests per carrier, store staging and production base URLs, run staging probes every 15 minutes, run production-safe probes hourly, assert status 200, required tracking fields, and latency under 800 ms, and open incidents with full response diffs and affected merchants.”
Payment sandbox monitor
Watch a payment partner before release.
“Build a payment API monitor that replays our saved authorization, capture, refund, and webhook verification requests every hour against the sandbox. Assert response shape, status, and latency under 500 ms, and open an incident with the diff when any assertion fails.”
Client status portal
Give each merchant its own integration history.
“Build a client status portal where each merchant signs in to see uptime, incidents, and probe history for its own integrations only. Send email updates when an incident opens, changes status, or resolves.”
Under the console
Probes are scheduled jobs. Each probe is a server-side function on a cron. It replays the saved request, evaluates the assertions, and writes the result as a row.
Partner keys stay server-side. Sandbox and production keys are stored by the platform and injected at run time. They do not live in exported collections, laptops, or wikis. A staging probe cannot run with production keys if you mark the environments separately.
Walls are data rules. An engineer scoped to two carriers gets two carriers back from the same tables. A client sees its own status view. The privacy rule is enforced before rows are served.
Because this is an app, it can grow surfaces a client can use: merchant status pages, weekly probe digests, and an agent that answers “when did the rate API last change?” from your own incident history.
Kliv also writes tests while it builds and can hold publishing until they pass. The testing page walks through that discipline.
Common questions
What exactly is Kliv?
Kliv is an AI app builder. You describe the API testing workflow you need, and it builds a real app with saved requests, probe schedules, incidents, diffs, and scoped views.
Do I get a real app, or a template?
A real app. Your endpoints, assertions, schedules, environments, incidents, and access rules are stored in a database built for your workflow.
Can I change it after it’s built?
Yes. You can add partners, assertions, schedules, incident fields, client views, or new environments by asking for changes in plain words.
Can probes run against production without causing damage?
Yes. You mark which saved requests are production-safe. Write-shaped requests can stay pinned to staging, and each environment carries its own keys.
Can clients see the workbench?
They can see a scoped view: their own integrations, incidents, uptime, and probe history. Engineers keep the full console.
What happens when an assertion fails at 3 a.m.?
An incident row is created with the response diff attached. Email or Slack can notify the on-call engineer, and the probe keeps running so recovery is recorded.
Can we import existing request collections?
Yes. Saved requests are data. Importing them gives them schedules, assertions, incidents, and access rules instead of leaving them as files on a laptop.
Can it store secrets safely?
API keys stay server-side and are injected when a probe runs. They do not need to be exported with request definitions.
Can I use my own domain?
Yes. Internal consoles and client status views can run on your own domain.
Can I move off Kliv later?
Yes. The app’s code syncs to your own Git repository, so leaving is a git pull rather than a rebuild.
Do I need a separate incident tool?
No, not for the workflow described here. Incidents can live in the same app as the probes, diffs, and client-visible timelines.
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Catch the version change before customers do
Describe how your team tests APIs — partners, requests, probes, assertions, and walls. Kliv builds the workbench that remembers it.
