API testing by an autonomous AI agent
Describe what your API should do. Qodex explores it, writes runnable HTTP test scenarios, and replays them on every change at zero LLM cost. Functional and security tests in one suite.
4.9 / 5 from 60 reviews on G2API testing is one module of Qodex, the agentic AI QA platform: the same autonomous agent covers UI testing, security testing, and PR review.
GET /v1/invoices/8412 as user B returned 200, expected 403. Cross-user read succeeded; finding filed with severity, repro steps, and evidence.
GET /v1/invoices/8412 Authorization: Bearer <user_b>
{ "invoice_id": 8412,
"customer": "user_a@example.com",
"total": 1840.00 }See the agent test a real API
Claims about AI testing are cheap. The test is whether an agent can take a plain-English request, write a runnable scenario, and produce a verdict you can check. Here is Qodex doing exactly that.
What is API testing?
API testing sends real HTTP requests directly at your endpoints and checks status codes, response bodies, auth behavior, and side effects, no user interface required. It applies to REST, GraphQL, and SOAP alike, and because it exercises the layer where your business logic and data live, it is faster and more stable than driving the same logic through a browser.
Qodex does it with an autonomous agent: you describe what to verify, it explores your API, writes the runnable test, and replays it deterministically on every change at zero LLM cost. It is the API surface of the wider agentic AI QA platform, and functional and API security tests live in the same suite.
Chat, scenario, deterministic replay
An autonomous agent replaces both the click-through-Postman-before-release job and the rotting-folder-of-scripts job with a three-step loop.
You describe the behavior in chat
Tell the agent what to verify in plain English. No DSL, no test-framework boilerplate. It already knows your endpoint inventory from your spec or from live exploration, so it starts with context.
The agent explores and writes a scenario
It resolves auth, then authors a structured scenario: a goal, ordered steps, and explicit assertions, plus a runnable script you can read and edit. New scenarios are auto-verified against your target on save; a human promotes drafts to active.
Replay is deterministic, and free
Once saved, a scenario is plain code: same requests, same assertions, no model in the loop. Your hundredth scenario costs exactly as much to rerun as your first, and every failure is triaged before it reaches you.
Every test checks more than "returns 200"
For each endpoint that matters, the agent drafts these six checks by default, including the tedious ones most hand-rolled suites skip.
| Status codes | The right code for valid and invalid input, not just a blanket 200 on the happy path. |
|---|---|
| Response body | The payload matches the expected shape and values, validated against the schema, not just any JSON. |
| Auth behavior | The endpoint rejects missing tokens and refuses data that belongs to another user. |
| Error handling | Bad input returns a structured error, not a stack trace or a 500 with a leaked detail. |
| Side effects | A successful POST is followed by a GET that proves the resource actually exists. |
| Response time | The endpoint answers inside its budget, so a slow regression is caught before users feel it. |
Start from OpenAPI, Swagger, or Postman
You do not start from a blank page. On import, Qodex reads your declared security schemes and infers how authentication works, so the agent arrives already knowing which endpoints exist, what parameters they take, and how to log in.
OpenAPI and Swagger
Import OpenAPI 3.x and Swagger 2.0 from a file or a URL. Qodex reads your declared security schemes and infers how authentication works.
Postman collections
Bring a Postman collection directly. Existing requests become the starting inventory instead of throwaway work, auth and all.
Live exploration
No spec? The agent explores the running app, captures endpoints, and builds the inventory from what the API actually exposes.
From there, the agent summarizes the endpoints, identifies the auth model, and recommends a testing strategy: which flows matter, which endpoints have no coverage, where the risky writes are. Coverage is tracked against the real inventory, not a test count. Coming from a Postman-centric workflow? The Postman alternatives guide walks through what the migration looks like.
Functional and security testing in one suite
The same agent writes both kinds of scenario against the same endpoint inventory. Alongside the happy-path and error-handling checks, it authors attack scenarios: broken object level authorization (BOLA), IDOR probes across user roles, auth bypass attempts, and injection payloads. Security scenarios use inverted semantics, where a pass means the attack was blocked, and the agent is built to never "fix" a failing security test by weakening its assertion.
The full methodology lives on the API security testing page, and the same scenarios run on every pull request as part of PR review.
Manual vs scripted vs agent-based API testing
The three approaches differ less in what they can test and more in who does the work and what happens when the API changes. Agent-based testing keeps the deterministic, scriptable execution underneath while moving the authoring and the upkeep to the agent.
| Manual (API client) | Scripted (code-first) | Agent-based (Qodex) | |
|---|---|---|---|
| Who writes the tests | A person, per request, per session | Engineers, in a test framework | The agent authors; a human reviews and promotes |
| Cost per rerun | Someone's afternoon | CI minutes | CI minutes; zero LLM cost on replay |
| When the API changes | Re-test by memory | Tests break; engineers patch them by hand | Failures classified as bug vs stale test; fixes suggested |
| Coverage growth | Flat; bounded by headcount | Linear with engineering time spent | Agent proposes tests for untested endpoints |
| Security testing | Separate tool, separate person | Rarely; needs specialist effort | Same suite, same agent, inverted pass/fail semantics |
| Scheduling and CI | None | Yes, wired by hand | Built in: cron schedules and webhook triggers |
For a tool-by-tool breakdown of the scripted and client-based options, see the comparison of API testing tools.
Run on a schedule, on a webhook, or on demand
Active scenarios run three ways. Because replay is deterministic, running the full suite on every deploy is an engineering decision, not a budgeting one.
On a schedule
Cron-based recurring runs: nightly regression, weekly security audit. Each schedule carries its own notification policy, so results reach the right email or Slack channel on the conditions you choose.
On a webhook
Your CI pipeline or deploy hook triggers a run with one HTTP call, authenticated by a per-project API key. Ship to staging, fire the webhook, get a verdict before promoting to production.
On demand
Ask the agent in chat to run a single scenario, a tagged subset, or the full suite, and watch the results stream in live.
Plans and usage caps are on the pricing page.
See pricingGenerated tests are real, ejectable code
There is no proprietary runtime and no opaque recording blob. Each scenario produces a standard executable script, parameterized by environment variables, that runs against any environment without modification. Engineers who want to read, edit, or version-control the tests can.
That means no code-level lock-in. If you leave Qodex, the tests leave with you: take the generated scripts and run them yourself at any time.
test('cross-user invoice read is refused', async () => { const res = await api.get('/v1/invoices/8412', { headers: { Authorization: `Bearer ${env.USER_B_TOKEN}` }, }); // inverted semantics: pass = the read was refused expect([403, 404]).toContain(res.status()); });
Go deeper on API testing
Guides on API testing types, strategies, and tools: how to pick tools, how to test REST and GraphQL APIs, how to fuzz for security, and how to keep a suite green in CI.
API testing FAQ
Comparing tools? See the best API testing tools roundup and the Postman alternatives guide.
API testing sends real HTTP requests at your endpoints and checks the responses: correct status codes, correct response bodies, correct auth behavior, and clean errors for bad input. It matters because the API is where your business logic and your data live, so a bug there is exposed to every client at once, and because catching it before production costs a fraction of catching it after. Testing the API directly is also faster and more stable than driving the same logic through a UI.
Your pipeline is continuous. Your testing should be too.
Import your spec or Postman collection, chat with the agent, and get a regression suite that replays at zero LLM cost.