# Steve Jobs Vision Prover MCP for AI Agents AI Agent Connect > Steve Jobs Vision Prover MCP. Stop letting your AI build feature factories. This tool forces your agent to kill unnecessary options, absorb complexity into the system, and focus on the human moment. It turns "AI-powered" specs into actual products by enforcing radical simplification and design taste. ## Overview - **Category:** engineering - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_utuErD2gnpH4HqP1nZAn2SOTR0g5vHhqwe0DBzRx/ai-agent-connect - **Tags:** steve-jobs, product-design, decision-pivots, structured-reasoning, focus, zero-configuration, ux-design ## Description Most people ask an AI to design a product and get back a bloated dashboard filled with settings menus and third-party integrations. It's a feature factory, not a product. This Connector changes that by forcing your AI client to think like a product leader who values subtraction over addition. Instead of just listing features, your agent has to name exactly what it's killing to make the experience better. It has to describe what the human feels without using tech jargon like "algorithms" or "APIs." It forces the system to make decisions for the user rather than pushing those choices into a dropdown menu. By using this Connector through the Vinkius catalog, you move from generating spec sheets to validating vision. The tool acts as a rigorous design review, rejecting any idea that relies on fragmentation or "configuration cowardice." It ensures your product owns the experience end-to-end and makes bold choices that actually matter. ## Tools ### validate_steve_jobs_vision Validates product ideas against five core design pivots to ensure radical simplification and taste. It rejects contradictory reasoning and coaches the AI to fix specific design failures. ## Prompt Examples **Prompt:** ``` I want to build a grocery delivery app that uses AI to help people eat healthier. What's the plan? ``` **Response:** ``` To make this a real product, we have to move past the 'healthy food dashboard.' **The Vision:** You open the app, and your next meal is already suggested based on your health goals and what's in your fridge. You just tap 'Confirm.' **What we're killing:** * **The Manual Meal Planner:** We're removing the ability for users to build complex weekly plans. The system will do this for them based on their goals. * **The Filter Menu:** We're removing 20+ filters for 'organic,' 'gluten-free,' etc. The system will prioritize these automatically in the feed. **The Moment:** You're tired after work. You don't want to think about dinner. You open the app, see a delicious, healthy meal that fits your diet, and click one button. Done. ``` **Prompt:** ``` We're building a project management tool for construction crews. They need to see their schedules and talk to each other. ``` **Response:** ``` We need to avoid the 'everything app' trap. A construction worker on a site doesn't want to navigate a complex project tree. **The Vision:** A single, high-contrast screen that shows exactly what needs to happen in the next 4 hours and who is responsible. **What we're killing:** * **The Gantt Chart View:** We're removing the complex timeline view. It's too much for a mobile screen in the mud. * **The Nested Folders:** We're removing the ability to organize tasks into infinite sub-folders. The system will group them by 'Active' and 'Pending.' **The Moment:** You walk onto the site. You look at your phone. You see: 'Pour concrete at Zone B - 10:00 AM.' That's it. ``` **Prompt:** ``` Help me design a new fitness app. It should have a lot of different workout types and a social feed. ``` **Response:** ``` If we include everything, we include nothing. A social feed and 500 workout types will bury the actual workout. **The Vision:** One workout that adapts to your current energy level. **What we're killing:** * **The Social Feed:** We're removing the infinite scroll of other people's workouts. It's a distraction. * **The Workout Library:** We're removing the choice of 500 types. The system will generate the optimal set based on your previous performance. **The Moment:** You're at the gym. You're tired. The app says: 'Do 15 minutes of mobility work.' You do it. You feel better. ``` ## Capabilities ### Kill unnecessary features Forces the AI to name specific removals and quantify how each one improves the user experience. ### Describe human moments Ensures the pitch focuses on what the human feels rather than technical specifications. ### Absorb system complexity Prevents pushing hard decisions onto the user by requiring the system to make them automatically. ### Define ownership boundaries Ensures the product owns the core experience without relying on third-party dependencies. ### Exercise design taste Forces the AI to make bold, polarizing choices instead of safe committee designs. ## Use Cases ### The Travel App A user asks to build a travel agent. The tool rejects the 15-API integration and forces an experience where the system knows the user's needs automatically. ### The Music App A user wants a music player. The tool validates a one-button experience where the system handles everything, killing search and playlists. ### The Hospital System A designer wants to manage room types. The tool forces a system that assigns rooms automatically based on data, removing 47 different options. ### The Luggage Brand A founder wants a smart bag. The tool rejects the IoT sensors pitch and forces a focus on a beautiful, durable box with one purpose. ## Benefits - Stop feature bloat by forcing the AI to name every feature it kills using validate_steve_jobs_vision. - Remove tech-first framing so your pitch focuses on human feelings instead of ML pipelines. - Eliminate configuration cowardice by forcing the system to make decisions instead of using settings menus. - Prevent fragmentation by ensuring your product owns the end-to-end experience without relying on third-party APIs. - Inject design taste into your product by forcing the AI to make bold choices that a committee would typically reject. ## How It Works The bottom line is that your AI stops guessing and starts making hard product decisions. 1. Provide your product idea or design pitch to your AI client. 2. The tool requires the AI to fill out reflection fields and commit to five specific decision pivots. 3. You get a VISION_PROVEN verdict or a specific coaching message on where the design is bloated or cowardly. ## Frequently Asked Questions **How does the Steve Jobs Vision Prover MCP help my product design?** It forces your AI to act as a rigorous design critic, ensuring your product is simple and focused. It pushes the AI to think about what to remove rather than just what to add. **Can this tool help me reduce feature bloat?** Yes, it requires the AI to explicitly name what it's removing and why that makes the product better. It prevents the AI from just listing features without thought. **What is configuration cowardice in the Steve Jobs Vision Prover MCP?** It is a design failure where the system pushes hard decisions onto the user via settings menus. The Connector forces the AI to make those decisions automatically for a smoother experience. **Does the Steve Jobs Vision Prover MCP work for hardware design?** It works for any product, including hardware, by focusing on the human experience and ownership. It ensures the core experience is owned end-to-end. **How does this tool handle third-party integrations?** It flags fragmentation if your product relies too much on external APIs for its core value. It forces the AI to own the experience rather than renting it from others. **Will the Steve Jobs Vision Prover MCP reject my ideas?** It will reject ideas that are bloated, tech-first, or lack clear design taste. It provides coaching to help you fix those specific issues. **Does it generate product designs?** No. It computes nothing and generates nothing. The LLM designs the product — this tool validates that the reasoning behind the design is rigorous. It catches contradictions: if the LLM claims zero configuration but describes a settings panel, the tool rejects and explains why. **What does it catch that a prompt instruction doesn't?** A prompt says 'think like Steve Jobs.' The LLM nods and generates bloated designs anyway. This tool forces the LLM to fill in specific fields — name what it killed, describe the human moment without tech words, explain how the system decides. Tool calls are obligations. Instructions are suggestions. The LLM cannot skip the reflection. **Can I use it for developer tools and APIs, not just consumer products?** Yes. The principles apply universally. A CLI tool with 47 flags is the same failure as a consumer app with a settings menu — you pushed decisions to the user. The 'experience backwards' pivot works for developers too: start with the developer's workflow, not your architecture.