---
title: Agent gateway | Qventis One
description: Coding agents create, update, select, run, triage and heal tests through MCP on the Qventis Engine, under your policy, with people approving every change.
---

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[Platform](https://qventis.ai/one?hsLang=en)/Agent gateway

# Agentic coding, with tests that keep up

Coding agents such as Claude Code, Copilot and Cursor use Qventis MCP tools across the whole test workflow: draft tests from a story or pull request, update them with the code, pick the smallest safe set, run them on the Qventis Engine, triage failures and propose heals. People approve every change.

[Book a demo](https://qventis.ai/contact#demo)

Get the brief

- The full test workflow, not just runs
- No agent approves itself
- Every call audited

**Agent gateway**MCP, CLI and API

Coding agentIDE, PR or CIMCP clientQVENTIS MCP TOOLScreate\_test\_from\_storyDraft plain-English tests from a story or PRupdate\_tests\_for\_diffUpdate steps the code change affectsselect\_tests\_for\_changePick the smallest safe set for this changerun\_suiteRun on the engine, zero AI tokenstriage\_failuresGroup failures by cause with evidencepropose\_healSuggest a fix, a person approvesgenerate\_test\_dataReserve or synthesize masked recordsquery\_quality\_pulseRead risk, readiness and alertsApprovalA person signsevery changeEngineDeterministic runevidence keptQuality ViewPulse, alertsand audit trail

Highlighted tools change tests and need approvalAgents propose, people approve

## What agents can do with your tests

Every tool works on the same App Model and plain-English steps your testers read, so agent work stays reviewable.

### Create tests from stories and PRs

Draft plain-English tests from acceptance criteria or a diff, ready for review.

### Update tests with the code

When a change renames a field or moves a step, the agent proposes the matching test update.

### Select the smallest safe set

Pick the tests a change touches, ranked by risk, instead of running everything.

### Run and read evidence

Runs happen on the engine with zero AI tokens. Agents read logs, screenshots and expected versus actual results.

### Triage by cause

Failures grouped into product defects, test issues and environment problems, with defects filed and evidence attached.

### Propose heals, never approve them

Fixes arrive with before and after evidence and wait for a person.

### Skills you can give your coding agents

1. **01**Write a plain-English test
2. **02**Map a diff to impacted steps
3. **03**Generate masked test data
4. **04**Explain a failure
5. **05**Review a proposed heal
6. **06**Check release readiness

## Security built into every call

The flowFrom change to approval

IdentityScoped sign-in per agent

PolicyChecked on every call

AuditEvery call on record

Three doorsCLI, HTTP API and MCP

### An agent verifies a change

A coding agent finishes a change and checks whether it broke anything. Every step is checked against policy.

- Signs in with its own scoped token
- Finds and runs the tests its change affects
- Reads the evidence and proposes a heal
- A person approves or rejects the heal

[Read: coding agents need a test gate](https://qventis.ai/blog/agents-need-a-test-gate?hsLang=en)

### Sign-in and allow-lists

Agents sign in with SSO and OAuth through your identity provider. You decide which actions each may take, and where.

- Scoped access for each agent
- Allow-lists per project
- Anything not on the list is denied

[See Trust & security](https://qventis.ai/platform/trust?hsLang=en)

### Policy and approvals

Each call is checked against role and attributes, the same way a person's request would be.

- Deleting tests needs a person
- Changing suites or shared components needs approval
- Heals and releases stay with people

[Read: earned autonomy for AI in testing](https://qventis.ai/blog/earned-autonomy?hsLang=en)

### Every call audited

Who asked for what, with which inputs and what result, exported to your SIEM.

- The same audit trail as people
- Runs tied to the change behind them
- Results in the same Quality View

[See Quality View](https://qventis.ai/one/quality-view?hsLang=en)

### Three doors, one policy

People, pipelines and agents reach the platform in different ways. The rules behind each door are the same.

- CLI for engineers and CI jobs
- HTTP API for pipelines, portals and scripts
- MCP for coding and chat agents

[See integrations](https://qventis.ai/platform/integrations?hsLang=en)

## Questions

Which agents work with it?

Any agent that speaks MCP, including Claude Code, GitHub Copilot and Cursor. CI pipelines use the CLI or HTTP API under the same policy.

Does an agent spend AI tokens when it runs tests?

Only its own, deciding what to call. The run itself uses zero AI tokens.

Can we limit an agent to one project?

Yes. Per-project allow-lists decide what an agent may do and where.

## Leave with one agent gated by policy

See one agent connected to one project, running tests under your policy.

[Book a demo](https://qventis.ai/contact#demo)

Get the brief

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