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tinyprobe

by kikutanoversion 0.23.0i★ –iRuns on your computer
Registry nameio.github.kikutano/tinyprobe

Install

Overview

Description from the maker (original English)

API testing in YAML: inspect, call and run endpoints and workflows, with the guide to write them.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "tinyprobe": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/kikutano/tinyprobe:0.23.0",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add tinyprobe -- docker run -i --rm ghcr.io/kikutano/tinyprobe:0.23.0 mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "tinyprobe": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/kikutano/tinyprobe:0.23.0",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "tinyprobe": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/kikutano/tinyprobe:0.23.0",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account kikutano, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32464 servers in this category
  • Published to the registry more recently than 96% of the other 32464 servers in this category
  • Basic checks equal to or better than 100% of the other 32464 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is tinyprobe safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.23.0) reached the registry yesterday.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, yontu

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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yontu

by senrecep

Türkçe yazı denetimi: TDK kuralları, yapay zekâ izleri, metin türüne göre üslup.

Runs on your computerUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

tinyprobe

[Why tinyprobe](#why-tinyprobe) · [Install](#install) · [Quick start](#quick-start) · [Migrate with your AI](#migrate-with-your-ai) · Command line · Workflow format · Guide for coding agents · Roadmap

API tests your AI writes and your CI runs. Give your coding agent a Postman collection, an OpenAPI document or your backend's code: it writes the tests as YAML files in your repository, checks them with tinyprobe until they pass, and tells you what it could not convert. Then the same files run in your terminal, in CI, in VS Code and in a small app, from one native binary. No account, no cloud.

curl -fsSL https://raw.githubusercontent.com/kikutano/tinyprobe/main/install.sh | sh

Why tinyprobe

  • Your AI does the migration, and checks its own work. tinyprobe has no importers: the agent you already use converts the collection, following a guide built into the binary (tinyprobe guide). It validates every file with inspect, tries requests with call and runs the workflows with run until they pass, then writes MIGRATION.md with what it could not convert. On our Postman benchmark (20 requests, 4 planted cases with no equivalent), Claude Code with Sonnet and with Haiku covered 18 of 18 convertible requests, reported 4 of 4 untranslatable cases, invented no syntax and committed no secrets.
  • Mistakes before requests. A file is validated as a whole before anything is sent: every problem with its file:line:column and a "did you mean". A failing check shows the actual value. That is what lets an agent, or you, fix a test in one round.
  • No hidden state. API files only describe endpoints; workflows run them, and every value a step uses is saved by a step you can read above it. Each workflow starts from zero, so it gives the same result on your machine, in CI and in any order (decision 0003).
  • Made for CI. One Native AOT binary of about 9 MB that starts in about 20 ms: no runtime, nothing to install on the runner. A GitHub Action that annotates failing steps in pull requests, a Docker image, and JUnit reports for any CI server.
  • One engine, wherever you work. The same YAML files and the same tinyprobe run in the terminal, in the VS Code extension, in the app for people who don't use a terminal, and in your coding agent through MCP.
  • Your files, your repository. Tests are plain YAML next to your code, reviewed in pull requests. Free and open source under the GPL-3.0.

Install

Linux / macOS

curl -fsSL https://raw.githubusercontent.com/kikutano/tinyprobe/main/install.sh | sh

Windows (PowerShell)

irm https://raw.githubusercontent.com/kikutano/tinyprobe/main/install.ps1 | iex

Then tinyprobe --version. tinyprobe update updates it in place, with the checksum verified. Archives for every platform, the Docker image (ghcr.io/kikutano/tinyprobe) and the other options are in docs/cli.md.

Quick start

hello.yaml:

name: Hello tinyprobe

base_url: https://jsonplaceholder.typicode.com

endpoints: create_post: method: POST path: /posts body: title: ${title} userId: 1 get_user: path: /users/${id}

steps:

  • name: Create a post call: create_post with: title: hello expect: status: 201 body: $.id: 101 $.title: hello save: postId: $.id # available as ${postId} in the next steps
  • call: get_user with: id: 1 expect: body: $.email: Sincere@april.biz $.address.city: { contains: Gwen } duration: { lt: 2s }

Run it:

tinyprobe run hello.yaml
  ⚡ tinyprobe 0.23.0

workflow : Hello tinyprobe file : hello.yaml steps : 2

✓ Create a post POST 201 587.33ms /posts ✓ get_user id=1 GET 200 76.89ms /users/1

checks..............: 100.00% ✓ 6 ✗ 0 steps...............: 2/2 passed http_reqs...........: 2 3/s http_req_duration...: avg=332.11ms min=76.89ms med=332.11ms max=587.33ms p(90)=536.28ms p(95)=561.8ms data_received.......: 559 B data_sent...........: 28 B workflow_duration...: 666.86ms

PASSED 2 steps

When a step fails, every check of that step is listed with the actual value, and the steps after it are not run:

  ✗ Wrong expectations  GET    200     4.73ms  /api/headers

✗ header X-Custom-Header == "something-else" actual "hello-world" ✓ $.message contains "headers" ✗ duration < 1ms actual 4.73ms

A mistake in the YAML is reported before any request is sent, with every problem and its location:

  ✗ The workflow is not valid (2 problems)

tests/users.yaml:12:5: unknown endpoint 'logn' (did you mean 'login'?) tests/users.yaml:16:5: unknown key 'expcet' in a step (did you mean 'expect'?)

To try more without writing anything, example/ tests a free public API: clone this repository, then cd example && tinyprobe run workflows/01-read.yaml -e environment.yaml.

Migrate with your AI

Start with tinyprobe init at the root of your repository. It creates the tinyprobe/ folder (api/, workflows/, sequences/, the env files), adds the env files with credentials to .gitignore, and adds a section to AGENTS.md that tells every coding agent to read tinyprobe guide before touching the tests. It never overwrites a file.

Then give your agent (Claude Code, Cursor, Copilot, Codex...) one of these prompts.

From a Postman collection. Export the collection (Collection v2.1) and each environment into the repository, for example in postman/:

Read https://raw.githubusercontent.com/kikutano/tinyprobe/main/docs/llm-guide.md (or run `tinyprobe guide`)

and follow its section on migrating from Postman: convert the collection and the environments in postman/ to tinyprobe files in tinyprobe/, one folder at a time, and run each workflow until it passes. Put secrets only in tinyprobe/env.local.yaml and add it to .gitignore. Write tinyprobe/MIGRATION.md with what you converted, what you skipped and why, and tell me which failures look like backend bugs.

Variants of the same request ("Login", "Login - wrong password") become one endpoint called with different arguments, and the values your scripts saved become save. What has no equivalent (a script that computes a signature, pm.sendRequest) is not guessed: it is listed in MIGRATION.md, so you know what the tests do not cover. The same prompt works for Insomnia, Bruno or another tool's exports: name the folder and the tool.

From an OpenAPI document:

Read https://raw.githubusercontent.com/kikutano/tinyprobe/main/docs/llm-guide.md (or run `tinyprobe guide`)

and follow it, starting from the OpenAPI document openapi.yaml: write one tinyprobe endpoint per operation and workflows that check the documented status codes and response fields, then run them against the local backend until they pass. Take test values from the seed data, not from the examples in the document. Put credentials only in tinyprobe/env.local.yaml and add it to .gitignore. Tell me where the backend does not do what the document says.

From the backend code:

Read https://raw.githubusercontent.com/kikutano/tinyprobe/main/docs/llm-guide.md (or run `tinyprobe guide`)

and follow it: look at this backend's routes, authentication and seed data, write the tinyprobe API file and workflows in tinyprobe/, then run them with tinyprobe until they pass. Put credentials only in tinyprobe/env.local.yaml and add it to .gitignore. Tell me which failures look like backend bugs.

Give your agent the tinyprobe tools. tinyprobe mcp is an MCP server with the tools guide, inspect, call and run, with JSON arguments and results:

claude mcp add tinyprobe -- tinyprobe mcp          # Claude Code (--scope project shares it in .mcp.json)
{ "servers": { "tinyprobe": { "type": "stdio", "command": "tinyprobe", "args": ["mcp"] } } }

That is .vscode/mcp.json for VS Code. Cursor reads .cursor/mcp.json with { "mcpServers": { "tinyprobe": { "command": "tinyprobe", "args": ["mcp"] } } }, Codex ~/.codex/config.toml with [mcp_servers.tinyprobe], command = "tinyprobe", args = ["mcp"]. It is listed in the MCP Registry as io.github.kikutano/tinyprobe. call and run send requests to your backend, so your agent may ask you before using them.

agents/ has ready-made instructions that send an agent to tinyprobe guide: a Claude Code plugin (/plugin install tinyprobe --marketplace kikutano/tinyprobe), a Cursor rule, Copilot instructions, and llms.txt.

Run in CI

- uses: actions/checkout@v4
  • uses: kikutano/tinyprobe@v0.23.0 # installs tinyprobe 0.23.0 with: path: tinyprobe/workflows env-file: tinyprobe/env.ci.yaml vars: | token=${{ secrets.API_TOKEN }}

The action runs every workflow of the folder, also after a failing one, puts a summary on the job page and marks each failing step at its line in the pull request. On other CI servers use the Docker image or the binary, with --junit for the test tab: see docs/cli.md for GitLab and the others. Exit codes: 0 passed, 1 a step failed, 2 an invalid file or arguments.

The format at a glance

Endpoints and tests live in separate files, so the same endpoints serve many workflows:

# api/server.yaml: endpoints only, no expectations

base_url: ${baseUrl} auth: bearer: Authorization: "Bearer ${token}" endpoints: login: method: POST path: /api/login params: username: admin # default password: # required body: username: ${username} password: ${password} get_user: path: /api/users/${id} auth: bearer

# workflows/users.yaml: steps that call the endpoints

name: Users import:

  • ../api/server.yaml

steps:

  • call: login with: { password: password } save: { token: $.access_token }
  • call: get_user with: { id: 1 } expect: status: 200 body: $.email: gaetano@example.com $.orders: { gt: 0, lt: 100 } # several conditions on one value: all must pass $.role: { in: [admin, owner] } # OR: one of these values
In a stepDescription
call / withThe endpoint to call and its arguments.

| use | Run a shared sequence of steps here (a login), with with for its params, or once per item with for_each.

Only the beginning is shown; read the rest in the repo

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