Revenue Multiple Valuator MCP for AI. Get an immediate, defensible range of enterprise value estimates.
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Revenue Multiple Valuator estimates SaaS company enterprise value using standard industry metrics. Input your Annual Recurring Revenue (ARR), growth rate, and Net Revenue Retention (NRR) to generate three valuation ranges—Bear, Base, and Bull scenarios.
The tool also benchmarks your performance against established market tiers.
What your AI can do
Calculate valuation scenarios
Calculates estimated enterprise value for Bear, Base, and Bull economic scenarios using your provided metrics.
Get performance classification
Classifies the company's financial health into specific qualitative performance tiers based on input data.
Retrieve multiplier matrix
Provides a transparent lookup table showing the hardcoded industry benchmarks used for all valuation calculations.
Calculate a range of potential enterprise values for Bear, Base, and Bull market conditions based on input growth rates.
Classify your company's financial health by comparing its metrics against qualitative industry performance standards.
Retrieve the underlying multiplier matrix to see exactly which industry benchmarks informed the valuation calculations.
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Revenue Multiple Valuator: 3 Tools
These tools allow you to calculate multi-scenario valuations, classify company health, and verify the underlying industry benchmarks for SaaS pricing.
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Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Revenue Multiple Valuator on VinkiusCalculate Valuation Scenarios
Calculates estimated enterprise value for Bear, Base, and Bull economic scenarios using your provided metrics.
Get Performance Classification
Classifies the company's financial health into specific qualitative performance...
Retrieve Multiplier Matrix
Provides a transparent lookup table showing the hardcoded industry benchmarks used...
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Claude AI
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Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Valuation used to feel like a messy, manual spreadsheet task.
Today, determining value means opening dozens of tabs. You copy-paste your ARR into one sheet, then manually look up industry multiples in another, and finally run sensitivity analyses across five different growth rates. It's slow, prone to formula errors, and always feels incomplete.
With this MCP, you eliminate the spreadsheet chaos. Instead of manually juggling multiple inputs, you provide your core metrics once. The system handles the complex modeling—running classification, cross-referencing multipliers, and calculating the full Bear/Base/Bull range—and gives you a clean, defensible output.
The Revenue Multiple Valuator MCP delivers immediate performance context.
You no longer have to guess which category your company falls into. You run `get_performance_classification` and immediately see if you're in the 'Steady growth' tier or something lower, giving instant qualitative feedback on your metrics.
What’s different now is that you get context first. The classification narrows your focus, allowing you to then use `calculate_valuation_scenarios` with much greater confidence in the range you present.
What your AI can actually do with this
Trying to figure out what a SaaS company is actually worth feels like guesswork until you run these numbers through the right model. This MCP connects your AI agent directly to financial modeling logic used by VCs and PE firms. You simply feed in key metrics—like current ARR, growth rate, and NRR—and it spits out an estimated enterprise value across three distinct economic scenarios: Bear (worst case), Base (most likely), and Bull (best case).
It doesn't just give you one number; it gives you a range based on established industry standards. You can also get immediate feedback on your company’s position by seeing how your specific metrics classify against peer performance tiers, giving you context that raw numbers alone miss.
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Here's how it actually works
The bottom line is you get an evidence-based range of potential value instead of a single, arbitrary number.
Supply your core financial data, including current ARR, growth rate, and NRR.
The MCP runs a classification check against historical performance tiers to contextualize your metrics.
It delivers three separate valuation estimates (Bear, Base, Bull) along with the multiplier matrix used for all calculations.
Who is this actually for?
Any founder or analyst who has to justify valuation in a pitch deck. If you're tired of building complex models on Google Sheets that only give one number, this is for you.
Using it to provide investors with a defensible range of value estimates rather than just a single valuation figure.
Benchmarking client performance by running their metrics against industry standards and identifying specific growth or retention weaknesses.
Quickly cross-referencing a target company's stated ARR and NRR to see if its reported valuation aligns with standard revenue multiples.
What Changes When You Connect
Move past single-number valuation pitches. By running the calculate_valuation_scenarios tool, you get three distinct estimates—Bear, Base, and Bull—giving investors a realistic risk spectrum.
Instantly benchmark your company's health. The get_performance_classification tool tells you exactly where you sit relative to industry peers in terms of growth and retention.
Stop arguing about the numbers. Use retrieve_multiplier_matrix to show stakeholders the exact, established industry benchmarks that drive every valuation calculation.
Simplify due diligence. You feed in basic metrics (ARR, NRR), and the system handles the complex financial modeling required for a professional assessment.
Understand risk context. The tool doesn't just calculate; it forces you to consider three economic outcomes, making your pitch much more credible.
See it in action
A founder needs to raise a Series B round.
The founder knows their ARR is solid, but the valuation range is tough. They run calculate_valuation_scenarios with various growth inputs, showing investors not just 'we are worth X,' but 'we are between $Y and $Z depending on market conditions.' This gives the board confidence in the potential upside.
An analyst is reviewing a competitor's pitch deck.
The analyst has only a company's stated ARR. They use get_performance_classification to gauge if that company’s reported growth rate and NRR are even in the 'Hypergrowth' tier, or if they fall into a less desirable segment.
A PE firm is modeling an acquisition.
The private equity team needs maximum transparency. They run calculate_valuation_scenarios and then immediately use retrieve_multiplier_matrix to verify that the assumed industry multiple (e.g., 5.0x) hasn't been changed or misrepresented.
The honest tradeoffs
Using only ARR for valuation
Assuming a company is worth $1M per dollar of ARR because they have high revenue, ignoring their retention rate and growth trajectory.
Never stop at just ARR. Run get_performance_classification first to determine if your NRR or growth rate puts you in the 'Exceptional' tier before running calculate_valuation_scenarios.
Forgetting economic variability
Presenting a single, static valuation number that fails when market conditions shift—a high-risk move.
Always use calculate_valuation_scenarios. This tool forces you to model the entire range: Bear, Base, and Bull. It's better to show a range than a single point.
Trusting an unverified multiple
Accepting a valuation figure from a pitch deck without knowing what market multiples were used.
Demand transparency. Run retrieve_multiplier_matrix to see the exact, hardcoded industry benchmarks that justify their requested valuation.
When It Fits, When It Doesn't
Use this MCP if your primary goal is building a defensible, multi-scenario range of enterprise value for SaaS businesses. Specifically, you need to answer: 'Given my metrics (ARR, NRR), what range of value should I expect across different market regimes?' If the answer is yes, run these tools. Don't use it if you only need a simple comparison against one or two direct competitors; those simpler tools are fine for that. If you just want to know 'is my revenue big enough,' that’s basic arithmetic and this MCP adds too much complexity. This tool is for advanced modeling where context (classification) and risk assessment (scenarios) matter as much as the raw numbers.
Questions you might have
How does calculate_valuation_scenarios work? +
It takes your ARR, growth rate, and NRR to estimate three distinct value ranges (Bear, Base, Bull). It's designed to show investors the full spectrum of risk inherent in the valuation.
What is the purpose of get_performance_classification? +
This tool classifies your company into specific performance tiers. It gives you qualitative feedback on whether your current metrics—like NRR and growth rate—place you favorably against industry norms.
Do I need to run retrieve_multiplier_matrix? +
It's best practice. Running retrieve_multiplier_matrix gives total transparency by showing the exact lookup table used for all valuation multiples, preventing questions about methodology.
Can calculate_valuation_scenarios handle different industries? +
The tool works across various SaaS models. However, remember to check retrieve_multiplier_matrix if you need to verify the specific industry benchmark being used for your calculation.
What format does `calculate_valuation_scenarios` expect for its inputs? +
It requires percentages as decimal values. You must input growth rates and Net Revenue Retention (NRR) as decimals (e.g., 40% becomes 0.40). The tool won't process whole numbers or text descriptions, so make sure your data is standardized before calling it.
If I run `get_performance_classification` with zero growth or NRR, will the tool fail? +
No, the classification handles zeros gracefully. Instead of failing, it assigns a specific tier reflecting stagnation. The output still gives you a clear performance status, which is useful for identifying companies that have plateaued.
Are there any rate limits when calling the valuation tools? +
Vinkius manages usage limits to keep things running smoothly. If you hit a temporary limit, your agent will receive an error code indicating how long you need to wait before retrying the call.
What data structure does `retrieve_multiplier_matrix` return? +
It returns the lookup table as structured JSON. This format makes it simple for your AI client to parse and map specific growth/retention combinations directly into valuation multiples, leaving no ambiguity about the source data.
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