One Rep Max Calculator MCP for AI. Predict your max lift capacity without lifting a single weight.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
One Rep Max Calculator estimates your true maximum weight capacity without needing to risk an actual max lift. It runs established scientific models—Epley, Brzycki, and Lander—against any set of weights and reps you input.
You can also calculate your current training load percentage to make sure every workout is hitting the right intensity zone.
What AI agents can do with One Rep Max Calculator Automation
Get brzycki estimate
Calculates your predicted 1RM using the well-known Brzycki formula.
Get epley estimate
Predicts your estimated 1RM using the Epley method, a popular standard in the industry.
Get lift intensity
Determines what percentage of your maximum strength you used for a given set.
Calculates your predicted one-rep max using three distinct, proven strength formulas.
Determines what percentage of your maximum capability a specific set represents.
Ask an AI about this
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What AI agents can do with One Rep Max Calculator with 4 Tools
These tools allow you to calculate estimated one-rep maxes using multiple established formulas, and determine your current lifting load percentage.
Make your AI actually useful.
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 One Rep Max Calculator on VinkiusGet Brzycki Estimate
Calculates your predicted 1RM using the well-known Brzycki formula.
Get Epley Estimate
Predicts your estimated 1RM using the Epley method, a popular standard in the...
Get Lift Intensity
Determines what percentage of your maximum strength you used for a given set.
Get Lander Estimate
Provides an estimated 1RM using the more advanced Lander/Lombardi statistical model.
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Built on the Model Context Protocol (MCP) for 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 4 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The Guesswork of Training Intensity, Solved with Vinkius AI Gateway
Right now, figuring out if your workout was hard enough is guesswork. You lift a weight, you note the sets and reps, and then you have to stop and calculate what that means relative to your actual max—a calculation fraught with manual effort and formula confusion.
With this MCP, the process changes completely. Input your session data once, and your agent instantly returns multiple scientific estimates of your maximum strength. You get a precise, quantifiable metric without doing any math yourself.
Get Multiple 1RM Estimates with One Click
Before this MCP, you might have to consult three different textbooks or online calculators, each using a slightly different formula (Epley, Brzycki, Lander), and then manually choose which one was most accurate for your specific lift.
Now, simply passing your data through the tool automatically runs it against all three models. You don't pick an estimate; you get three objective numbers to analyze and build a stronger program around.
What your AI can actually do with this
You don't have to bust out on a max lift attempt just to know how strong you are. This MCP lets you predict your one-repetition maximum (1RM) safely and accurately. By connecting this tool through Vinkius, your agent takes your known workout data—like 'I lifted 100kg for 5 reps'—and runs it against multiple established formulas.
Instead of guessing or relying on memory, you get three different scientific estimates: one using the Epley method, another using Brzycki’s approach, and a third using Lander’s model. It also determines your training intensity percentage so you know exactly what kind of load you're working with. You just input the numbers; the MCP handles the complex math.
019ed92a-7911-70bf-a778-e6c50ea66b2a Here's how it actually works
The bottom line is you get multiple, science-backed predictions of your strength without ever having to lift the weight in person.
You tell your AI client the weight and number of repetitions you completed during a workout.
The MCP runs that data through the selected mathematical model (Epley, Brzycki, or Lander).
It delivers a predicted 1RM value, allowing you to compare estimates from different scientific methods.
Who is this actually for?
Anyone who coaches or trains serious athletes needs this. If you're constantly cross-referencing different 1RM formulas or wasting time on manual calculations, this MCP saves your time and improves the accuracy of your client programming.
Determining a client’s peak strength potential quickly before designing a cycle of progressive overload.
Checking their training load percentage after an unexpected workout to ensure they aren't dropping below optimal intensity zones.
Calculating estimated lifting capacity for a patient whose current lifts are limited by injury, ensuring the prescribed weight is appropriate but challenging.
What Changes When You Connect
Accurate comparison: You don't have to pick just one formula. By running data through both get_epley_estimate and get_brzycki_estimate, you get a range, giving you more reliable training targets for your athlete.
Know your load instantly: Use get_lift_intensity anytime. If your client lifted 80kg when their max is 100kg, this tells you immediately they hit an 80% intensity zone—no manual math needed.
Comprehensive modeling: Getting estimates from three distinct methods (get_epley_estimate, get_brzycki_estimate, and get_lander_estimate) hedges against formula bias, giving you the most robust potential number.
Save time on programming: Instead of spending minutes cross-referencing textbook formulas for your client, this MCP gives you instant 1RM predictions based on real workout data. This is a huge workflow win.
Targeted training: Use the calculated intensity to adjust sets dynamically. If the tool shows they were at 65% load last week, you know exactly where to push them this week.
See it in action
Recalibrating a client's goals after an injury setback
A coach needs to adjust program weights for a lifter who can no longer perform heavy sets. By inputting the current manageable weight and reps, the agent uses get_epley_estimate to calculate a safe, conservative 1RM estimate. This allows the coach to restart programming immediately without guessing.
Comparing lift performance across different training cycles
A powerlifter wants to know if their current training block is progressing optimally. They input data from two weeks ago and today into get_brzycki_estimate. Comparing the two predicted 1RMs gives them clear, quantitative proof of whether their effort worked.
Checking workout quality mid-session
During a high-volume session, an athlete wants to know if they hit their target intensity. They run the weights used against get_lift_intensity. If it shows 75%, they confirm they nailed the session's goal without stopping for calculations.
Determining a starting weight for a new trainee
A coach has a brand-new client with limited history. Instead of making assumptions, the coach uses get_lander_estimate on an initial warm-up set to establish a scientifically defensible baseline 1RM.
The honest tradeoffs
Using only one formula
Relying solely on the Epley method when your client's training history suggests Brzycki is more accurate for their sport. This leads to potentially inaccurate programming.
Always check multiple models. Run the data through get_epley_estimate, get_brzycki_estimate, and get_lander_estimate to get a reliable range, not just a single number.
Forgetting training load
Just logging the weight lifted without knowing what percentage of their max that was. The coach thinks 80kg is good enough when it's actually too light.
After every session, run your weights through get_lift_intensity. This immediately tells you if you hit your target load (e.g., 'Did I hit 85%?') or if you dropped below it.
Manual calculation errors
Trying to calculate the 1RM manually in a spreadsheet and messing up the exponentiation or ratio setup.
Let your agent handle the math. Use get_brzycki_estimate or any of the dedicated model tools for perfect, reliable calculations every time.
When It Fits, When It Doesn't
Use this MCP if your goal is to estimate maximum strength capacity based on known set weights and reps. This tool excels at providing comparative predictions using established formulas like get_epley_estimate or determining current training intensity via get_lift_intensity. It's perfect for coaches who need quick, data-driven feedback during programming.
Don't use this if you need to track historical performance (i.e., comparing a lift today vs. 6 months ago on video footage) or manage client records outside of the calculation itself. For pure record keeping, a dedicated database tool is better. This MCP only calculates potential; it doesn't store history.
Questions you might have
How accurate is the One Rep Max Calculator using get_epley_estimate? +
It provides a scientifically recognized prediction, but remember it's an estimate. The Epley method is popular because it’s straightforward and reliable for general programming adjustments.
Do I need to know my actual 1RM before using get_brzycki_estimate? +
No, you don't. You only need the weight and reps you actually lifted in a given set; the tool calculates your estimated max from that data.
What is the difference between get_lift_intensity and 1RM prediction? +
Intensity measures load percentage (e.g., '85% of maximum effort'). 1RM tools predict the absolute weight number you can lift once.
Can I use this MCP for different types of lifts, like pulling movements? +
The models are general enough to handle various compound strength movements. Just ensure your input data (weight/reps) is consistent with the type of lift you're tracking.
Does get_lander_estimate use a different math than Epley? +
Yes, it uses a more complex statistical model that factors in multiple variables. This often provides a unique perspective compared to simpler ratio methods like the Epley formula.
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