Multimeter is Git-native API testing in VS Code. Requests, tests, mocks, and docs are YAML .mmt files in your repo.
Start with a single HTTP request. Grow into tests, suites, mocks, reports, documentation, and CI when you need them.
All in the same tool. No migration. No second product.
🎯 What you get
Simple by default
- ✔️ Git-native, file-based YAML
- ✔️ Lightweight — no account, no cloud lock-in
- ✔️ Collaboration through pull requests, like code
- ✔️ The same files locally and in CI
A full testing platform when you need it
- ✔️ HTTP, WebSocket, GraphQL, and gRPC
- ✔️ Multi-step flows and test suites
- ✔️ Mock servers
- ✔️ Generated documentation
- ✔️ Reports
- ✔️ CI with
testlight
AI in the same files
- ✔️ Generate tests from an API or a description (Cursor, Copilot, Claude via MCP)
- ✔️ Judge replies — semantic similarity, or open-ended checks like how funny a response is
- ✔️ Bring your own model (Ollama or cloud)
- ➕ More features
🪜 Start simple, grow easily...
Multimeter is a VS Code-native extension. All you need is:
- Click Install button in Multimeter VS Code Extension
- Open Get Started from the activity bar and follow the instructions
There you run a POST request as follows:
type: api
title: Simple POST
url: https://test.mmt.dev/echo
method: post
format: json
body:
message: hello
That's enough for manual API testing. Need automated tests?
Type the following to test if the status is 200.
type: test
steps:
- http: https://test.mmt.dev/echo
method: get
expect:
status: 200
- Still simple.
- Still Git-native.
- Still easy to review.
As your project grows, Multimeter grows with it.
- Test suites
- Mock servers
- Documentation
- Workflow execution
- Structured reporting
- CI artifacts
- & More...
Add only when you need them. Everything stays in the same ecosystem.
🤖 MCP, AI generation, and AI judges
Cursor, Copilot, and Claude write and run the same .mmt files you edit in VS Code. MCP (mmt-mcp) gives them scaffold_test, validate, format, and run — generate tests from an API or a description, then keep them in Git.
Judge an API answer in the same test. Compare semantic similarity to an expected reply, or check something open-ended — for example, how funny the response is. Bring your own model (Ollama or cloud). An alternative to a separate Promptfoo eval stack.
See MCP docs · Judge docs
🔁 Built for reliable CI
Multimeter validates test definitions before execution.
That means:
- Earlier feedback
- More deterministic execution
- Fewer surprises in CI
- Easier debugging
- Reproducible results
GitHub Actions:
- uses: actions/checkout@v4
- uses: mshobeyri/testlight-action@v1
with:
file: tests/suite.mmt
report: junit
report-file: results/junit.xml
Or from a terminal using the Multimeter CLI called testlight.
npm install -g mmt-testlight
testlight run tests/suite.mmt
Why Git?
Your code, tests, mocks, documentation, reports, and environment settings live in the same repository.
- Version controlled
- Code and tests evolve together
- Reviewable through pull requests
- Easy to move and share
- No platform lock-in
- AI can update code and tests together
- Environment variables never go missing
- Historical test results stay with the project
🧠 Philosophy
Most API tools focus on requests. Multimeter focuses on behavior.
Instead of asking:
"Did this request return the expected response?"
Multimeter helps you answer:
"Does this system still behave correctly?"
Licensed under Apache 2.0.
Demos · Documentation · Website
