# Founder Vision Prover MCP > Founder Vision Prover forces your AI client to stop flattering you and start stress-testing your business idea like a top venture capital firm. It validates five critical startup pillars: proving real customer pain, calculating market size from the ground up, modeling true retention rates, establishing zero-cost distribution loops, and proving financial viability in under 12 months. ## Overview - **Category:** business-strategy - **Price:** Free - **Tags:** startup, venture-capital, y-combinator, founder, unit-economics, retention, distribution ## Description Running an idea by a standard AI model usually results in fluff—suggestions like "run Facebook ads" or citing massive, unproven market figures. This MCP changes that. It forces the agent to act as a ruthless venture partner who only cares about numbers and verifiable customer behavior. Instead of vague praise, it demands evidence: Show us the exact workaround customers are paying for today. Calculate your total addressable market by multiplying reachable users by annual contract value. Prove retention using Month 3 cohort data, not just signups. Model how a user brings in the next customer at zero cost. And finally, show that your unit economics will pay back acquisition costs within a year or two. Getting this level of strategic rigor used to require a team of analysts; now, you can execute the full evaluation flow directly through Vinkius and connect it to any MCP-compatible client. ## Tools ### validate_founder_vision Runs a deep, structured analysis on any startup idea, verifying its core viability across five financial and behavioral criteria. ## Prompt Examples **Prompt:** ``` I want to build a better CRM. The global CRM market is $50B according to Gartner. If we capture just 1% we'll be a unicorn. We'll acquire users via Google Ads and hire a sales team. ``` **Response:** ``` TOP_DOWN_DELUSION + DISTRIBUTION_NAIVE — "Gartner says $50B" is top-down nonsense. Count the ACTUAL reachable customers and multiply by your price. And "Google Ads + sales team" is a double tax — both scale linearly with spend and decay with competition. Define a structural $0 CAC loop or accept you're building a lifestyle business. ``` **Prompt:** ``` Restaurant managers pay an intern $1k/month to update inventory in a Google Sheet every night. We charge $200/month. 15,000 mid-market restaurants in the US × $2,400/year = $36M TAM. Month 3 retention: 85%. Gross margin: 92%. Each restaurant invites their suppliers to the platform (network effect), driving CAC to $0. CAC: $300, payback: 1.5 months. Crossover: month 14. ``` **Response:** ``` VISION_PROVEN — Founder Vision Validated. Behavioral pain: intern hack exists ($1k/month waste). Bottom-up TAM: 15,000 × $2,400 = $36M. Retention: 85% M3 (above 80% SaaS threshold). Margin: 92%. Distribution: supplier network effect drives CAC toward $0. Unit economics: 1.5-month payback, crossover at month 14. Execute. ``` **Prompt:** ``` Users are annoyed that they have to use two different apps to book flights and hotels. We will build an all-in-one travel app. We have 50,000 downloads and a waitlist of 10,000 people. ``` **Response:** ``` BEHAVIORAL_VOID — "Annoyed" is not a venture-scale pain. Customers are NOT hacking a solution — they are not paying interns or duct-taping spreadsheets to combine flight and hotel bookings. This is a vitamin, not a painkiller. And 50,000 downloads and a waitlist are vanity metrics — they prove interest, not retention. Show Month 3 cohort data. ``` ## Capabilities ### Validate Core Customer Pain Forces the AI agent to identify concrete evidence that customers are currently paying for a workaround solution. ### Calculate Bottom-Up Market Size Determines realistic market potential by multiplying specific customer counts by annual revenue, bypassing inflated industry reports. ### Prove Retention Physics Examines whether the product retains users past the initial hype cycle using cohort analysis and margin calculations. ### Identify Structural Distribution Loops Determines if user growth relies on intrinsic virality or if it requires continuous, paid spending. ### Model Unit Economics Viability Calculates the time needed for a new customer's revenue to cover their acquisition cost against defined burn rates. ## Use Cases ### Pitching to VCs A founder runs their pitch deck through the MCP. The agent immediately flags that while the market sounds huge, they haven't calculated the true reachable customer base and therefore fails the Bottom-Up TAM test. ### Evaluating a New Vertical Market A product strategist inputs an idea for industrial automation. The MCP doesn't accept 'AI will solve this.' Instead, it demands proof that facility managers are already wasting time/money on manual workarounds today. ### Stress-Testing Internal Bets A company leadership team submits a new internal project idea. The MCP forces them to model the unit economics, showing that if they spend too much to acquire users, they'll run out of capital before hitting profitability. ### Revising an Existing Business Model A company with high user signups but low retention runs the MCP. The agent flags 'Retention Death,' forcing the team to rebuild their product around core feature usage rather than just marketing hype. ## Benefits - It forces the agent to validate behavioral evidence, moving you past 'I think people are frustrated' into 'Here is what they pay for today.' - You ditch top-down thinking. The MCP only accepts Bottom-Up TAM calculations: reachable users multiplied by annual contract value. - Stop worrying about vanity metrics like downloads. This tool demands Month 3 cohort retention proof to validate product stickiness. - It rejects paid ads as a growth plan, forcing you to define a structural distribution moat that keeps your customer acquisition cost at zero. - You get immediate unit economics clarity. It calculates if your customer payback period is less than twelve months, preventing slow capital burns. ## How It Works The bottom line is that you get an instant, highly technical assessment that tells you exactly which pillar of your business model needs fixing before you spend another dollar on ads. 1. Input your business concept, including initial market assumptions and growth plan. 2. The MCP executes a five-point structural review, forcing the agent to fill out fields for customer hacks, bottom-up TAM calculations, M3 retention proof, $0 CAC methods, and payback timelines. 3. You receive a definitive verdict—either 'Vision Proven' with actionable numbers or one of five fatal startup physics failures. ## Frequently Asked Questions **How does Founder Vision Prover work with my current business plan?** It takes your core idea and forces it through a five-part validation sequence, demanding proof for customer pain, market size, retention, distribution moats, and unit economics. **Can Founder Vision Prover tell me how big the market is?** It doesn't use general market reports. Instead, it calculates Bottom-Up TAM by making you multiply the specific number of reachable customers by your annual contract value. **Does Founder Vision Prover accept paid advertising as a growth strategy?** No. It automatically flags reliance on paid ads as Distribution Naivety, forcing you to identify an intrinsic user loop that generates new users at zero cost. **What is the difference between this MCP and just asking ChatGPT for ideas?** ChatGPT gives vague praise. This MCP forces rigorous financial testing. It demands specific metrics like M3 cohort retention or CAC payback < 12 months, making it a true validation tool. **How often should I use Founder Vision Prover?** Use it every time you finalize a core assumption about your business model. Don't assume anything; let the MCP force you to prove it. **Does it predict if my startup will succeed?** No. It validates STARTUP PHYSICS — the structural mechanics that make venture-scale growth possible. If your cohort retention leaks, your CAC payback is too slow, or your distribution is paid ads, no amount of vision will save the business. This tool stops the AI from flattering your bad ideas. **Why does it reject 'downloads' and 'signups' as proof of retention?** Downloads, signups, and waitlist size are vanity metrics. They measure interest, not retention. The only metric that proves retention is COHORT data: of users who joined in Month 1, what percentage are STILL ACTIVE in Month 3? If you cannot answer that, you have a leaky bucket. **What is a 'Behavioral Hack'?** If a problem is truly painful, the customer is already solving it TODAY using a hack — spreadsheets, interns, duct tape, custom scripts. They are spending money or time on an absurd workaround. If they are NOT hacking a solution, the pain is not real enough to justify a purchase.