Incrementality Estimator MCP for AI. Prove your campaigns generated lift, not just revenue.
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Incrementality Estimator calculates true marketing ROI by proving campaign lift above what would happen naturally. It uses control group data to establish a baseline conversion rate first, then determines the absolute and percentage gain from your advertising spend.
This gives you an accurate return on ad spend (ROAS) figure that isn't inflated by organic activity.
What your AI can do
Calculate baseline metrics
Required before any lift calculation can begin.
Calculate baseline conversion rates for control and exposed groups
Calculate incrementality metrics
Determines how much better the exposed campaign performed versus what would have happened without it.
Calculate incrementality metrics including absolute lift, percentage lift, and incremental CPA
Calculate roas comparison
Calculate true incremental ROAS and compare it to reported channel ROAS
It calculates the natural conversion rates for both the exposed and control groups, setting a standard for comparison.
The system measures how much better your ad-exposed group performed compared to the baseline—providing absolute and percentage uplift figures.
It converts the calculated lift into a genuine Return on Ad Spend, providing an actionable profitability metric.
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Incrementality Estimator: 3 Tools
These tools guide you through a three-step process: establishing baselines, quantifying uplift, and calculating final ROAS comparison.
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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 Incrementality Estimator on VinkiusCalculate Baseline Metrics
Required before any lift calculation can begin. Calculate baseline conversion rates for control and exposed groups
Calculate Incrementality Metrics
Determines how much better the exposed campaign performed versus what would have...
Calculate Roas Comparison
Calculate true incremental ROAS and compare it to reported channel ROAS
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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.
Every marketing dashboard shows a different story.
Today, reporting is messy. You spend hours cross-referencing spreadsheets: one tab for the ad-exposed group, another for the control group, and then manually trying to figure out what was *new* revenue versus what would have happened anyway. This guesswork means your executives often get misleading numbers.
With this MCP, you give your agent both data sets at once. It automatically establishes that baseline conversion rate first. The result is a clean comparison showing only the lift—the proven activity that required spending money.
The Incrementality Estimator provides true ROAS.
You stop having to manually calculate absolute and percentage lifts. The system handles this complex math, providing a single figure for the total incremental volume generated by your campaign.
It’s simple: you get one number that accurately represents how much every dollar spent actually mattered.
What your AI can actually do with this
Standard Return on Ad Spend (ROAS) is flawed; it treats every single conversion as a campaign win. But much of that traffic would have converted anyway, regardless of your ads running. This MCP solves for that baseline noise. It establishes statistical proof of lift by comparing performance against an untreated control group.
You pass in the raw data from both groups, and the system isolates the absolute activity strictly attributable to your campaign treatment. The result is a genuine marginal return figure—a true ROAS number you can use to make budget decisions. Vinkius hosts this MCP so your agent client connects once and gives you access to this critical analysis right alongside other analytics tools.
019ecb74-2ce4-731d-bf42-6441377c5c61 Here's how it actually works
The bottom line is you move beyond simple reporting; you quantify the exact monetary value of your intervention.
First, run calculate_baseline_metrics by supplying data from both your exposed group and the untreated control group to establish the natural conversion rate.
Next, feed those baselines into calculate_incrementality_metrics. This calculates the absolute lift volume and percentage uplift that only the campaign generated.
Finally, pass the incremental volume and total spend into calculate_roas_comparison to get a true ROAS number for decision-making.
Who is this actually for?
Anyone responsible for justifying marketing budgets. This is for the Performance Marketing Manager who needs to prove ROI, or the Growth Lead frustrated by misleading dashboards that overstate campaign success.
Uses this MCP when they need to defend budget allocation during a review. They require proof of lift beyond simple ad spend metrics.
Runs deep comparative analyses comparing test group performance against untouched control groups, needing precise metric outputs for modeling.
Needs to pinpoint which specific campaigns created new revenue vs. just capitalizing on existing brand awareness.
What Changes When You Connect
Stop basing budgets on inflated data. By running calculate_baseline_metrics, you establish a clear natural conversion rate for comparison.
You isolate the true gain by using calculate_incrementality_metrics. This reveals the absolute and percentage lift attributable only to your campaign, filtering out organic activity.
It gives you actionable financial data. The final step, running calculate_roas_comparison, provides a marginal ROAS figure that justifies spend.
The workflow is built for accuracy. You don't have to manually track control groups; the MCP guides the process from baseline through final comparison.
This eliminates 'vanity metrics.' Instead of just reporting ad spend vs. revenue, you report proven incremental value.
See it in action
Budget Justification After a Campaign
The Performance Manager needs to justify a $50k campaign spend. They run calculate_baseline_metrics first, then use calculate_incrementality_metrics on the results. The final ROAS comparison proves that the campaign delivered 120 truly incremental conversions, securing the next quarter's budget.
Evaluating a New Channel
A Growth Lead wants to know if a new social channel is genuinely effective or just capturing existing traffic. They feed the data into calculate_baseline_metrics and then use calculate_incrementality_metrics to see if there's any lift above historical performance.
Comparing Campaign ROI Across Channels
You need one number to compare Google Ads vs. Facebook Ads accurately. You run the full sequence: baseline, incrementality, and then calculate_roas_comparison for both channels. This ensures you're comparing true lift, not just gross revenue.
Troubleshooting Low ROAS Reports
The marketing team reports low ROI, but the spend was high. Instead of panicking, they use calculate_roas_comparison to check if their standard reporting is mixing up incremental value with baseline activity.
The honest tradeoffs
Running simple ROAS reports
The team looks at total ad spend and divides it by all conversions. This gives an artificially low CPA because it includes people who would have converted anyway.
Don't use standard reporting. First, run calculate_baseline_metrics to find the natural conversion rate. Then, use calculate_incrementality_metrics before running calculate_roas_comparison. This forces you to measure lift only.
Ignoring the control group
The analyst only focuses on the exposed group data and assumes all conversions are due to the campaign. They miss out on measuring natural market behavior.
You must include the untreated control group data in calculate_baseline_metrics. This is the necessary first step that provides context for every conversion number.
When It Fits, When It Doesn't
Use this MCP if your goal is to prove causality, not just correlation. You need a verifiable metric of 'lift'—the difference between campaign performance and what happened naturally. Don't use it if you simply need to count total conversions or calculate basic CPA from one single data set. If all you have are gross conversion numbers without any control group data, this MCP won't solve the problem; you need to collect that foundational A/B test data first.
Questions you might have
What is the difference between reported ROAS and true incremental ROAS? +
Reported ROAS treats all conversions as campaign-attributable, which usually overestimates value. True Incremental ROAS uses the calculate_roas_comparison tool to factor in the baseline conversion rate derived from the control group, providing a much more accurate measure of marginal return.
I only have raw cohort sizes and conversions. What should I run first? +
You must start by using the calculate_baseline_metrics tool. This establishes the fundamental conversion rates (Control CR and Exposed CR) needed for all subsequent lift calculations.
How do I find the absolute number of extra conversions? Which tool handles this? +
The calculate_incrementality_metrics tool is designed for this. It takes your baseline CR and exposed performance data to calculate the absolute incremental conversions, telling you exactly how many extra sales were achieved.
If I have missing or null data points when using `calculate_baseline_metrics`, how will the tool handle it? +
The function requires all specified inputs (group sizes, conversions) to be numerical. If required fields are null or non-numeric, the MCP throws an error and stops processing. You must pre-validate your raw data before running this initial calculation.
What should I do if `calculate_incrementality_metrics` returns values that seem statistically unreliable? +
Small sample sizes often lead to volatile lift figures. While the tool can process low volumes, we recommend analyzing groups with a minimum of 100 users each for stable and actionable incrementality metrics.
Does running `calculate_roas_comparison` require that I first run all three tools in sequence? +
No, the comparison tool is robust enough to take necessary inputs directly. However, we strongly suggest using calculate_incrementality_metrics beforehand because it validates and optimizes your lift figures for accurate ROAS modeling.
What data format or prerequisites are needed before I can start with the initial step: `calculate_baseline_metrics`? +
You need two specific sets of raw numbers: the total user count and total conversion count for both your exposed group and your control group. These counts must cover the identical time period you want to analyze.
If I run multiple comparisons in a session, are there rate limits when chaining `calculate_incrementality_metrics` with `calculate_roas_comparison`? +
Vinkius manages usage rates automatically. For heavy or continuous analysis, you may encounter throttling errors. Batching your calls or scheduling the processing will help prevent hitting platform-level usage limits.
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