TestSprite generates tests in its cloud. agent-qa learns in your repo.
TestSprite focuses on autonomous generation and cloud verification. agent-qa turns agentic QA into explicit YAML, hooks, memory, and evidence that stay with the code your agents change.
Try agent-qa, the source-available way to turn generated QA into remembered evidence.
agent-qa vs TestSprite
| Capability | agent-qa | TestSprite | Details |
|---|---|---|---|
| Source access | TestSprite is not positioned as a repo-owned framework with published source, so behaviour you disagree with is a support ticket. With agent-qa it is a pull request. | ||
| Repo-owned YAML | TestSprite keeps the test intent inside its own product. agent-qa keeps intent, config, hooks, memory and suites beside the code they cover, where your engineering process already works. | ||
| Coding-agent native | A coding agent cannot click through a hosted editor. agent-qa ships MCP tools, packaged Skills and a CLI, so the agent that changed the code writes the test, runs it and reads the failure without leaving the loop. | ||
| Bring your own LLM | Whoever picks the model sets your quality ceiling and your bill. agent-qa lets you point at any provider, any compatible endpoint, or a model on your own hardware, and change it in one line. | ||
| Local and CI execution | One command on a laptop, in CI, and from an agent. No run depends on somebody else's control plane being up, and nothing queues behind another tenant. | ||
| Web and mobile QA | Web, Android and iOS from the same natural-language flow and the same evidence model. The surface is a target named in a file, not a different product tier. | ||
| Memory, cache, hooks | Execution memory, a validated action cache and sandboxed hooks compound. A suite that has been running a month is faster, cheaper and better informed about your app than the day it was written. | ||
| No platform lock-in | Every durable asset stays in your repository. Cancel agent-qa tomorrow and the tests, the memory and the evidence are still there and still readable. |
Why teams switch from TestSprite
Built for coding agents, not dashboards
Your team already ships code with coding agents, and a coding agent cannot click around TestSprite's interface. agent-qa ships MCP tools, packaged Skills and a CLI, so Claude Code, Cursor and their peers author the test, run it and triage the failure inside the same loop that wrote the change.
Your tests stop being hostages
Every test you write in TestSprite makes leaving TestSprite more expensive. That is not an accident, it is the business model. Every test you write with agent-qa is a YAML file in your repository: reviewed in a pull request, portable to any runner, and still yours the day you cancel.
Generated tests you can't review are liabilities
Autonomous generation without code review produces coverage you can't reason about. agent-qa keeps generation agentic but lands every test as reviewable YAML in a pull request, so a human (or another agent) can see exactly what's being promised.
TestSprite automates testing into its cloud. agent-qa automates it into your codebase, where review, memory, and your coding agents already live.
Frequently asked questions
Is agent-qa a good TestSprite alternative?
Yes, and the reason is structural rather than a feature count. TestSprite is an autonomous testing platform that generates and verifies tests in the vendor's cloud, which means the asset you are building lives on their side of the line. agent-qa is a source-available QA agent with no paid tier, governed by FSL-1.1-ALv2: tests are plain-English YAML in your repository, runs execute on your laptop, in your CI, or from your coding agent, and every run writes back into memory committed beside the tests. The suite gets better at your app whether or not you renew anything.
How much does agent-qa cost compared to TestSprite?
TestSprite is priced on cloud platform subscriptions, so the bill tracks how much you test. agent-qa has no paid tier, no seats and no platform fee; FSL-1.1-ALv2 governs permitted use. You pay for the model tokens and infrastructure you already control, on the provider you choose, and the validated action cache takes roughly 60% of the tokens off a matched rerun. Adding coverage does not add a line item.
How do I migrate from TestSprite to agent-qa?
You are re-describing intent, not porting code, which is why this is far smaller than a normal test migration. Export the intent of your TestSprite coverage, what each generated test verifies, and re-state it as agent-qa YAML flows your team reviews once and owns forever. Run npx agent-qa init, write each critical flow as a plain-English YAML test, and let the runtime work out the selectors and the recovery. Most teams move a smoke suite in an afternoon, and there is nothing to un-pick later because the output is files in your own repository.
Does agent-qa cover web and mobile like TestSprite?
Yes, and from the same file. agent-qa runs end-to-end tests on web, Android and iOS with one natural-language format, one memory store and one evidence model, so a flow written once survives being pointed at another surface. agent-qa runs mobile E2E natively alongside web; generated or hand-written, the tests share one repo-owned format.
Can coding agents generate agent-qa tests the way TestSprite generates tests?
Yes. That's the native workflow. agent-qa ships MCP tools and packaged Skills so Claude Code, Cursor, and similar agents can author tests from product context, validate them, run them, and file the results, with everything landing in your repo instead of a vendor cloud.
Sources
This page is based on public product and documentation sources. Verify current features and pricing with each vendor before making a purchase decision.
Where agent-qa pulls ahead of TestSprite
The parts of agent-qa that answer what TestSprite leaves you carrying.
Natural-language tests
Write actions and assertions in plain English; agent-qa resolves them against the live interface.
Learn about natural language testsPlain-English YAML
Describe the behavior once; it stays as reviewable YAML in your repository.
Learn moreExecution memory
Turn successful runs into reviewable, evidence-backed memory that makes every future run faster.
Learn about memoryProven before it is used
New knowledge must pass replay and live evidence before guiding a run.
Learn moreFaster warm runs
Reuse proven flows and supersede stale facts instead of rediscovering them.
Learn moreA run leaves evidence
Elements that resolved, a flow that worked, and timings that are real, all attached to the steps that produced them.
Version controlled, built for teams
Tests, knowledge, and rules stay as reviewable files shared by teammates, agents, and CI.
Learn about configurationFiles, not a database
Tests, config, memory, and rules stay as files your team can inspect and own.
Learn moreLearning arrives as a diff
New memory and issues arrive as pull-request diffs, with their evidence.
Learn moreOne commit everywhere
Humans, coding agents, and CI share the same knowledge from one commit.
Learn more- Tests
- Configs
- Memory
- Self improvement
- Knowledge
- Engineeragent-qa
- QA engineeragent-qa
- Coding agentagent-qa
- CIagent-qa
Bring your own model
Switch providers, endpoints, or models in config without rewriting a single test.
Learn about LLM providersUse your existing seat
Run with supported Codex or Claude Code subscriptions, with no second bill.
Learn more
Compatible endpoints and Codex subscription workflows.
Compatible endpoints and Claude Code subscription workflows.
Gemini configs with named credentials.
Cloud and open model workflows through compatible endpoints.
Open model workflows through compatible endpoints.
Cloud and open model workflows through compatible endpoints.
Cloud model access through compatible endpoints.
Local models through compatible endpoints.
Desktop local model workflows via compatible servers.
Route compatible requests across a broad hosted model catalog.
MiMo model workflows through compatible endpoints.
Hunyuan model workflows through compatible endpoints.
DeepSeek model workflows through compatible endpoints.
GLM model workflows through compatible endpoints.
MiniMax model workflows through compatible endpoints.
Nemotron open models through compatible endpoints.
Step model workflows through compatible endpoints.
Ling open models through compatible endpoints.
* This comparison is based on publicly available information. Product capabilities and pricing can change; verify details with each vendor before making a purchase decision.