
VaporMock
Describe your API. Get a live URL. Instantly.
What it does
Describe your API in plain English. Get a live URL instantly. Build your frontend without waiting for the backend.Stop waiting for backend teams. VaporMock uses AI to generate realistic mock APIs from plain English descriptions. Just type "I need a list of 50 users with Indian names" and get a deployed, ready-to-use API endpoint in seconds. Perfect for frontend devs and prototyping.
Does a similar job
all alternatives →


apimock-rsNov 2025 · apimokka.github.io · ▲9A developer-friendly, fast and functional HTTP(S) server.
- AAAPIMock – API Mock server with domain support and proxy to record mocks2020 · github.com · ▲6
- AGAuto-generate load tests/synthetic test data from OpenAPI spec/HAR file2024 · docs.multiple.dev · ▲33
Hey HN, We just shipped a new AI-powered feature... BUT the "AI" piece is largely in the background. Instead of relying on a chatbot, we've integrated AI (with strict input & output guardrails) into a workflow to handle two specific tasks that would be difficult for traditional programming: 1. Identifying the most relevant base URL from HAR files, since it would be tedious to cover every edge case or scenario to omit analytics, tracking, and other network noise. 2. Generating synthetic data for API requests by passing the API context and faker-js functions to GPT-4. The steps are broken down…
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 18d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 19d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 28d ago · cactuscompute.com

