Connect any AI agent through the KomAInu MCP server
Point Cursor, Claude, Codex, OpenCode, or any MCP-capable agent at the KomAInu MCP server. Each agent gets the same coverage context and testing skills, so you keep your preferred tool.
KomAInu·Solution
AI Test Case Generation from Requirements
KomAInu turns your requirements into test cases automatically: an agentic AI that generates the missing test code needed to cover your SRS, ready for an engineer to review.
What is AI test case generation?
AI test case generation uses an AI agent to turn software requirements into concrete test cases and test code. Instead of writing every test by hand, engineers let the agent read the SRS, understand each requirement’s expected behavior, and produce the tests needed to verify it. For critical software teams, automated test case generation is the fastest way to close coverage gaps without sacrificing the requirements traceability matrix or control.
Writing test cases by hand does not scale
Manual test authoring is slow, and the tests that are never written are exactly the ones that fail an audit.
Slow to write by hand
Authoring a test for every requirement, edge case and boundary condition ties up engineering time on every certification cycle.
Missing tests go unnoticed
Requirements without tests stay invisible until an audit or a production bug reveals the gap.
Coverage that can't keep up
As requirements evolve, manual test suites fall behind and coverage silently degrades.
How KomAInu generates your test cases
KomAInu provides an MCP server that lets your AI agents read coverage analyses, write the missing tests, and sync updated coverage results back into KomAInu after human review.
Generate test code, then sync coverage back to KomAInu
Your agent writes the missing tests from KomAInu's gap report. After review, coverage results update automatically in the KomAInu application, so the console stays aligned with what is actually verified.
Built for critical software
Agentic AI test automation designed for regulated environments where every generated test must be traceable and reviewable.
To catch requirement violations before merge, use the automated compliance review workflow.
Compatible with your standards
Generated tests fit the requirement structure of DO-178C, ISO 26262, EN 50128 and IEC 62304.
Your data never leaves
KomAInu is model-agnostic and can run on-premise, so your SRS, tests and code never reach an external model provider.
The engineer stays in control
Every generated test case is proposed for human review. The AI accelerates the work; the engineer approves it.
Frequently asked questions
What is AI test case generation?
It is the use of an AI agent to turn requirements into concrete test cases and test code, instead of writing every test by hand.
How does KomAInu generate test cases from requirements?
KomAInu reads the requirement, identifies the expected verification scenarios, detects which are missing, and generates the test code needed to cover them.
Does automated test case generation replace engineers?
No. KomAInu proposes generated tests for review. Engineers stay in control and approve every test that enters the repository.
Can KomAInu fix existing tests, not just create new ones?
Yes. Beyond generating new tests, KomAInu can fix or complete existing test code to close coverage gaps.
Which AI agents work with the KomAInu MCP server?
Any MCP-capable agent: Cursor, Claude, Codex, OpenCode, and others. They all retrieve the same coverage context and testing skills from KomAInu.
Do coverage results update in KomAInu after tests are generated?
Yes. After an engineer reviews and approves the generated tests, coverage results sync back into the KomAInu application so the console stays aligned with what is verified.
What languages and test frameworks does it support?
KomAInu adapts to your existing test repository and its frameworks, so generated tests fit the code your team already maintains.
Can it run with open-source or on-premise AI models?
Yes. KomAInu is agnostic to the underlying AI model and can run with open-source models hosted on your own infrastructure.
Model selection
Small model plus fusion beat a frontier model
Before generating missing tests, KomAInu first needs reliable requirement-test links. TraceFuse explains the benchmark behind that traceability engine and why method design mattered more than model size.
Read the TraceFuse benchmarkGenerate the tests you’re missing
Talk to our team about automated test case generation for your DO-178C, ISO 26262, EN 50128 or IEC 62304 project.
See how the traceability matrix works