Why I Built TiefWise

I’ve been using Postman for years, and I used to complain a lot about it. At some point I stopped complaining and thought: let me just build my own REST client for personal use.

The moment I realized my data wasn’t mine

Back then, Postman was free. I logged in with my personal email and started building collections. Everything synced automatically — including API keys and tokens. At the time it felt convenient.

But later I realized something unsettling. When I logged into Postman on my personal machine, I could see all my company collections and secrets outside the corporate network. I hadn’t even noticed it happening. API keys, bearer tokens, internal endpoint URLs — all sitting on a third-party server, accessible from anywhere. That’s not a feature. That’s a security incident waiting to happen.

That’s when I made the first decision: everything stays local. No cloud. No accounts. No sync you didn’t ask for. Your data lives on your machine, under your control, always.

The collaboration mess

Day to day, I work with many APIs — different versions, different teams, different modules. Everyone had their own collections. Sharing usually happened over chat or email, often with keys still in them. Very quickly, I had duplicates everywhere, no idea which one was the latest, too many tabs open, and a lot of rework.

That’s when I thought: why can’t we just version-control this? If collections lived in Git, developers and QE teams could always pull the latest version — no confusion, no rework. It would save a massive amount of time.

So I built TiefWise around standard file formats. Collections are JSON files on disk. Export them, commit them, share them, diff them — they work with the tools you already have. No proprietary sync layer needed.

The bloat problem

Another issue was that Postman tries to serve everyone — developers, QA, leads, managers. I didn’t need all those features. I just wanted fast debugging: see headers, timing, compare responses, export to cURL, and move on.

Over the last two years, I slowly added exactly those features to my own tool:

• cURL in, cURL out — because that’s how developers actually share API calls. Paste from Slack, export to docs, drop into CI scripts. No translation needed.
• Response comparison — when something breaks after a deploy, I don’t want to stare at two JSON blobs. Show me what changed. Color it. Filter the noise.
• Request timing and headers — the full picture of what happened between me and the server. No hidden redirects, no swallowed errors.
• Environment switching — dev, staging, production. One click. No editing URLs by hand. No “wrong environment” postmortems.
• Ctrl+F in responses — sounds basic, but I was opening DevTools just to search a JSON payload from my own API tool. That’s embarrassing.
• Undo delete — because one misclick shouldn’t wipe out an hour of careful organization.

Nothing revolutionary. Just the things I actually needed, built fast, without the weight of features I’d never use.

The credential problem nobody talks about

Once I started sharing collections with teammates, I noticed how often API keys slipped through. Someone exports a collection, posts it in a channel — production credentials included. It happens because humans forget. Every time.

So I built Secret Guard — automatic credential detection and redaction on export. It scans for API key patterns, bearer tokens, AWS credentials — and strips them before the file leaves your machine. Not because developers are careless. Because safe defaults protect everyone.

The offline reality

I travel. I work from planes, trains, coffee shops with unreliable WiFi. A cloud-based API tool that shows a loading spinner when you’re offline is useless exactly when you need it most.

TiefWise works fully offline. Open it, see your collections, review your history, prepare requests. Because your saved work shouldn’t need an internet connection just to be visible.

Then came AI agents

Over the last year, while working on AI agents, I had another realization: agents are the next API consumers. They need to discover endpoints, understand parameters, and make calls — just like developers do. But nobody was making that bridge easy.

That’s when I built mrapids CLI — an MCP server driven directly from OpenAPI specs. Point it at a spec file, and AI agents get callable tools automatically. No manual wiring.

Then I brought that same idea into TiefWise: take a working collection — endpoints you’ve already tested and refined — and generate an MCP config from it. Your existing work becomes AI-accessible. Three steps, no rewriting.

The spec import gap

Working across teams, I constantly received OpenAPI specs and Swagger files. “Here’s our API” — great. Now I have to manually recreate every endpoint in my tool? That’s transcription, not engineering.

So I built one-click spec import. OpenAPI 3.x, Swagger 2.0 — drop it in, get a ready-to-use collection. Path params, auth schemes, body schemas — all extracted. Because the machine-readable contract should actually be read by the machine.

Why I’m sharing it

At that point, I checked with colleagues, searched the internet — and realized this wasn’t just my problem. Developers everywhere were hitting the same friction:

• Credentials leaking through shared exports
• Collections locked behind subscriptions
• Tools too bloated for simple debugging
• No bridge between API collections and AI agents
• No way to version-control API workflows with Git

So I decided to share it.

What TiefWise is — and isn’t

Honestly, my goal is not to replace Postman. They serve a different audience — teams that need collaboration dashboards, API monitoring, mock servers, documentation portals.

I built TiefWise for the developer who just wants a light, fast, simple tool for APIs.

• Free. No accounts. No subscriptions. No “upgrade to unlock.”
• Local-first. Your data never leaves your machine.
• Fast. Opens instantly. No cloud sync delay. No loading spinners.
• Secure by default. Credentials auto-redacted on export. SSRF protection built in.
• AI-ready. Your collections can become MCP tools for agents.
• Git-friendly. Files on disk. Commit them. Diff them. Share them.

If you want a full platform with team management, API governance, and enterprise dashboards — that’s not what this is.

If you want a tool that respects your time, your data, and your workflow — that’s exactly what this is.