Detect Product-Market Fit Signals Using MCP.
Tech stack analyzed, company growth verified, traction signals scored , verify product-market fit from the outside before you write the check
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Here is what the tech stack tells you that the pitch deck never will. Your AI agent queries BuiltWith for the startup's domain , acmepayments.com.
BuiltWith returns the full technology fingerprint: Frontend: React, Next.js (modern stack , good). Hosting: AWS (standard). Analytics: Segment, Mixpanel, Google Analytics (triple-layered analytics means they are measuring everything , PMF-seeking behavior).
Payments: Stripe, Stripe Billing (they are charging customers , revenue exists). Support: Intercom (they have enough users to need support tooling).
CRM: HubSpot (they have a sales process). Marketing: Customer.io, Google Ads (they are spending on acquisition). Error tracking: Sentry (they care about production reliability).
That tech stack tells a story: this is a company that is charging customers, measuring usage, supporting users, running a sales process, and investing in acquisition.
That is operational maturity consistent with early PMF. Now compare that to the second Seed company you are evaluating , CompetitorX.com: Hosting: Vercel.
Analytics: Google Analytics only. Payments: none detected. Support: none. CRM: none. That is a landing page, not a product. Clearbit adds the quantitative layer: Acme has 42 employees (up from 28 six months ago).
Estimated revenue: $4-6M. CompetitorX has 8 employees and no revenue signal. The agent builds a Google Sheets PMF scorecard: 12 signals measured, scored 0-3, composite PMF confidence score.
Acme scores 31/36 (high PMF evidence). CompetitorX scores 8/36 (pre-PMF). You know which check to write.
Connector Orchestration: 3 Connectors, one intelligent agent
Connect BuiltWith, Clearbit and Google Sheets Connectors so your AI agent analyzes a startup's technology stack through BuiltWith (what tools they use, what analytics they run, what payment systems they integrated), enriches the company profile through Clearbit (employee count, estimated revenue, growth trajectory), and compiles a product-market fit evidence report in Google Sheets. Every Seed founder says 'We have strong product-market fit.' But PMF is not a feeling , it is a set of observable signals. A company running Stripe billing + Segment analytics + Intercom support + HubSpot CRM is operationally mature. A company with only a landing page and Google Analytics is still pre-product. Your agent reads the signals the founder cannot hide.
Builtwith Tech Lookup
triggerAnalyzes the startup's technology stack, analytics, payments and infrastructure
lookup_domain_tech get_domain_company_info get_domain_trust get_domain_keywords Clearbit Hubspot
actionEnriches company profile , employee count, revenue estimate, growth signals
find_company find_person_and_company autocomplete_company find_risk Google Sheets
actionCompiles the PMF evidence report with scoring
create_spreadsheet append_sheet_values update_sheet_values get_spreadsheet Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own Connector
Convert any internal API into a Connector. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Builtwith Tech Lookup, Clearbit Hubspot & Google Sheets ready in the catalog right now
- Add more from 5,800+ servers whenever you need
- Connections are secured and compliant by default
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added weekly
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 5,800+ Connectors and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across all tools, in one conversation. That's what this connectivity layer was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across all platforms.
Contextual Reasoning
Each decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your Connectors once, and your agent handles the rest. Each time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius AI Connectors to handle these for you. You describe what you need. It does the rest.
Seed-stage VCs performing pre-meeting diligence who want to verify product-market fit claims before scheduling a partner call with the founder
Angel investors evaluating 10+ deals per month who need a rapid, data-driven way to separate companies with real traction from companies with just a pitch deck
VC associates building deal screening reports who need external signals to supplement the founder's self-reported metrics
Accelerator selection committees reviewing applications who need a scalable method to verify which applicants have shipped a real product versus a prototype
Frequently Asked Questions About This Connector Orchestration
Which Connectors do I need for this workflow?
Three: BuiltWith, Clearbit and Google Sheets. Connect all three to your AI client before running any prompt from this page.
Does this work with Claude Desktop, Cursor or Windsurf?
Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others. Connect the Connectors and paste a prompt.
Can a startup hide their tech stack?
Partially. Some technologies are visible in the page source (JavaScript libraries, analytics scripts, payment embeds). Server-side technologies are harder to detect. BuiltWith catches what is client-visible , which covers most SaaS tooling. A startup that actively hides their tech stack is unusual and worth asking about.
Is the PMF score reliable?
The score measures observable operational signals , not product-market fit directly. A high score means the company has built infrastructure consistent with having paying customers and a real product. It is a proxy, not a guarantee. Use it to prioritize due diligence, not to replace it.
Can I customize the scoring criteria?
Yes. Tell the agent your priorities. If you weight payment integration 5x over analytics, the scoring adjusts. The framework is flexible , your investment thesis determines the weights.
Does this work for B2B and B2C startups?
Yes, but the signals differ. B2B startups show CRM, billing, and support tools. B2C startups show analytics, ad platforms, and engagement tools. Adjust your scoring criteria based on the business model.
Run Technical Due Diligence Using Connectors
Funding data pulled, tech stack analyzed, diligence report built , evaluate startup infrastructure without asking for a demo
Screen Accelerator Applications Using MCP
10,000 applications received, companies verified, fake traction filtered , shortlist the real startups from the noise in hours, not weeks
Spot Competing Startups Using Connectors
Tech stacks compared, market overlap mapped, duplicate startups flagged , catch two batch companies building the same product before Demo Day embarrasses everyone
Connectors for Investment Committee Memos
Company enriched, funding history pulled, IC memo structured , your investment committee prep goes from 8 hours to 30 minutes
Connectors to Match Founders With Peer Networks
Cohort companies profiled, mutual-benefit pairs identified, peer introductions sent , activate the most powerful part of your program: founders helping founders
Benchmark Seed Valuations Using Connectors
Your portfolio valuations compared, market comps pulled, benchmark report built , know if $12M pre-money for a Seed is reasonable before you negotiate
Connectors used in this workflow
BuiltWith Tech Lookup
BuiltWith Tech Lookup gives your AI agent the ability to see exactly what tech powers any website. Instead of guessing, your agent can identify CMS platforms like Shopify or WordPress, find hidden analytics trackers, and map out hosting providers or CDNs. It turns your AI into a technical architect that can audit digital infrastructure in seconds.
Clearbit (HubSpot)
Clearbit (HubSpot) MCP lets you enrich lead data directly from your AI agent. It pulls professional details, firmographics, and company insights using just an email or domain. It is built for anyone who needs to turn raw contact info into actionable B2B intelligence without switching tabs.
Google Sheets
Google Sheets MCP lets you read, write, and manage spreadsheet data through your AI agent. Stop wasting time on manual data entry or complex formulas. Just tell your agent to pull specific ranges, add new rows, or create entire new sheets on the fly. It handles the tedious work of keeping your data organized so you can focus on making decisions.