AI-powered REST Client and API testing in VS Code. Git-native alternative to Postman. YAML .mmt files.

Demo · Website · Request Feature · VS Code · CLI · GitHub Action · Docs · llms.txt

Multimeter — Get Started, YAML, and API tester

🚀 Start with a request. Grow into a platform.

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)

See all features →

⚡ Start simple

Multimeter is a VS Code-native extension. All you need:

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.

No suites.
No mocks.
No workflows.
No complexity.

🧪 Need tests?

type: test
steps:
  - http: https://test.mmt.dev/echo
    method: get
    expect:
      status: 200

Still simple.
Still Git-native.
Still easy to review.

🚀 Scale without switching tools

As your project grows, Multimeter grows with it.

Add:

Test suites
Mock servers
Documentation
Workflow execution
Structured reporting
CI artifacts

Only when you need them.

Everything stays in the same ecosystem.

See all examples →

🤖 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

See the GitHub Action and Testlight install.

📦 Everything stays in 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?"

License

Multimeter is licensed under the Apache License 2.0.

Demos · Documentation · Website · GitHub

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