Once you connect Claude, ChatGPT, or another AI tool to FitMetrics via MCP, the most important question becomes: what do you ask it? This article is a prompt playbook — real coaching use cases you can copy-paste into your AI tool today.
All of these prompts work out of the box with a FitMetrics MCP API key. The AI tool will chain the right read and write tools automatically.
New to MCP? Start with our setup guide first.
Morning coaching routine
A 5-minute briefing before you open your inbox.
"Give me a morning briefing: which of my clients are waiting for a reply, who needs follow-up, and who had a great workout yesterday?"
"Which clients missed their daily nutrition log yesterday?"
"Summarize all AI form submissions from the last 24 hours that haven't been reviewed."
"Pull my team's activity log for the last 24 hours — who did what?"
Prepping for a client check-in
Before you message a client, have the AI assemble everything you need to know.
"I'm about to check in with Sarah. Pull her last 2 weeks: compliance, nutrition averages, workouts completed, any missed sessions, and the last 10 messages. Then draft a check-in message."
"Summarize Mike's Zoom call from last Tuesday — action items, commitments, and anything I promised to follow up on."
"What did John say in his most recent AI form submission, and how does his current compliance match what he said?"
"Read Kate's WHOOP data and nutrition for last week. Is there a recovery/intake mismatch I should flag?"
Updating a client's macros (new)
The AI can adjust a client's Trainerize macros directly. The change is pushed to Trainerize instantly and shows up in the client's app for their next meal log.
"Xenios was 400 calories over target every day this week. Drop him to 1800 calories with 200g protein."
"Set Sarah to 2200 calories, 180g protein, 250g carbs, 60g fat."
"Increase Mike's calories by 150, keep protein the same, add the difference to carbs."
"Look at the last 4 weeks of John's weigh-ins and nutrition. If he's losing too fast, bump calories up by 100. If too slow, cut by 100."
Safety: You'll see the AI's recommended change before it executes in tools that preview tool calls (like Claude Desktop). The change is logged with a full audit trail.
Scheduling macro cycles (new)
FitMetrics can schedule future macro changes and apply them automatically at a date and time you choose (in your business's timezone). Use this for diet breaks, refeed weeks, phase transitions, and planned cut/bulk bumps.
"Put Sarah on a 4-week cut starting next Monday at 7am — 1800 calories, 200g protein, 120g carbs, 60g fat. Four weeks later, schedule a refeed week at 2400 calories with 200g protein."
"Schedule a diet break for every client on a cut: two weeks from today, bump them up 300 calories. Two weeks after that, drop them back to their original target."
"Show me every pending scheduled macro change for John — I want to make sure there's nothing conflicting with the new plan."
"Cancel all scheduled macro changes for Mike — we're rethinking his plan."
"Look at Sarah's compliance over the last 4 weeks. If she's hitting above 85%, schedule a -100 calorie drop for next Monday. If below, schedule a +100 bump instead."
How it works: The AI uses schedule_macro_change to queue the change, list_scheduled_macro_changes to see what's pending, and cancel_scheduled_macro_change to remove one. FitMetrics's hourly cron applies the change at the exact local date and time and pushes the new goal to Trainerize.
Saving coach-visible notes (new)
Give the AI durable memory by asking it to save notes to the client's profile. These appear in the FitMetrics Messages > Notes panel and are shared across all message threads.
"Review Sarah's last 2 weeks of nutrition and workouts, then save a pinned note summarising what's working and what to change."
"Write a note on John's profile: 'Reported left knee discomfort on 2026-04-17 — swap barbell squats for goblet or split squats this week.'"
"After every AI form submission, save a one-paragraph summary as a note on that client so I can see context without re-reading the form."
"When I ask 'what does the coach need to know about Kate', pull her pinned notes first."
Pipeline, tasks, and follow-ups (new)
Use your connected AI to manage CRM state — moving clients through your pipeline, flagging for follow-up, and keeping a clean task list.
"Move Sarah to the Onboarded stage and create a task for me to call her next Friday."
"Read Mike's last 5 messages. If anything sounds like a concern, flag him for follow-up."
"Create a task: 'Review John's form submissions from this week', priority high, due tomorrow, assigned to me."
"Go through my to_do tasks from before today and mark any that are still relevant as in_progress; complete the rest."
"For every client whose program expires this month, flag them for follow-up AND create a renewal task."
"List every client who has been stuck in the 'Questionnaire' stage for more than 7 days and flag them for follow-up."
How it works: Uses move_client_to_stage, update_client_followup, create_task, and update_task_status. Pair with list_stages and list_tasks to read current state before changing it.
Habits (new)
FitMetrics can assign and remove Trainerize habits for your clients. Habits appear in the client's Trainerize app and are tracked daily with streak counts. Your connected AI can see them, set them up, and tear them down.
"Assign the 'Eat vegetables at every meal' habit to Sarah for 4 weeks, Monday through Friday."
"For every client on a cut, assign the 'Drink only zero calorie drinks' habit for 8 weeks."
"Show me Mike's current habits. If any have hit a 30-day streak, remove them and tell me which ones so I can celebrate with him."
"Create a custom habit for Kate: '10-minute morning walk', starting tomorrow, 6 weeks, every day."
"Audit all my clients' current habits — anyone with more than 3 active habits should drop their lowest-streak one."
How it works: get_client_habits lists current/upcoming/past habits with streak data, assign_habit_to_client adds a habit with type + name + schedule + duration, and remove_habit_from_client deletes one (validated against the client). Common habit types: eatVeggie, eatProtein, drinkOnlyZeroCalorieDrink, prepareYourOwnMeal, practiceEatingSlowly, prioritizeSelfCare, digitalDetoxOneHourBeforeBed, and customHabit for anything custom.
Bulk / cohort actions
Coaching leverage — one sentence, many clients.
"Send a congratulations message to every client who hit a workout PR this week."
"Find all clients whose program expires in the next 14 days and schedule a re-sign message for each of them for Monday at 10am."
"List every client below 70% compliance for the last 4 weeks and schedule a check-in AI template to each."
"For every client with the tag 'cutting', review their weight trend and adjust calories by no more than 100 in either direction."
Weekly macros: training vs rest, refeeds, carb cycling (new)
One step up from daily macros: your connected AI can set different calories and macros for each day of the week. Great for training vs rest day splits, refeed days, and carb cycling blocks.
"Put Sarah on a training/rest split: Mon/Wed/Fri 2500 cal 220P 280C 60F, Tue/Thu/Sat/Sun 2000 cal 220P 160C 70F."
"Set John's macros so Sunday is a refeed day at 2800 calories, and every other day stays at his current 2200."
"Carb cycle for Mike for the next 4 weeks — high carb Mon/Wed/Fri, low carb the rest, all at 200g protein."
How it works: set_client_weekly_macros takes a daily_targets object with all 7 days. Mode (full_macros / calories_protein / calories_only) is auto-detected based on what you send and must be consistent across all 7 days. The weekly plan is saved to FitMetrics and today's target is pushed to Trainerize; subsequent days apply automatically by the daily sync.
AI form submission review (new)
When an AI agent reads, summarizes, and responds to an AI form submission, have it close the loop by marking the submission reviewed — so human coaches don't double-handle.
"For each unreviewed AI form submission from this week: read the responses, write a short summary, draft a reply message to the client, and mark the submission reviewed when done."
"Un-mark Sarah's form submission from yesterday — I want to re-review it myself."
"Mark every submission older than 7 days as reviewed so my queue is clean."
How it works: list_form_submissions with reviewed: "not_reviewed" to find candidates, then mark_submission_reviewed(submission_id) to close each. Pass reviewed: false to unmark.
Managing messaging workflows
"Draft a birthday message for every client with a birthday this week, and schedule each for 9am on their birthday in their local timezone."
"Reply to Mike's last message with something encouraging and reference a specific workout he completed yesterday."
"Check my scheduled messages for this week and cancel any that look like duplicates."
AI check-in templates & automations
Meta-coaching: use your connected AI to build the AI check-in templates that automatically message your clients later.
"Create an AI check-in template called 'Weekly Nutrition Review' that uses calorie data and gives one actionable tip."
"Assign the 'Motivational Coach' AI check-in template to every client with less than 60% compliance, send every Tuesday at 9am."
"Enable the daily Trainerize sync automation at 6am in my timezone."
"Turn off the weekly Trainerize summary automation until I re-enable it."
Diagnostics & research
Use your connected AI as a read-only analyst over your whole business.
"Which coaches on my team have the highest and lowest average client compliance for the last 30 days?"
"Cross-reference WHOOP recovery with workout adherence across all my clients — is there a correlation?"
"Pull the transcripts of my last 10 Zoom calls with clients and tell me what the most common objections or friction points were."
"How many messages per week do I send on average? How does that compare to my team members?"
Tips for getting the best results
Ask the AI to chain steps. Instead of 'get Sarah's data' then 'write a note', say "pull Sarah's nutrition and workouts, then save a pinned note summarising trends". The AI will call the read and write tools in one go.
Use names the AI can look up. If you say 'Sarah', the AI will call
list_clients(search="Sarah")first. Full names are safest.Preview write actions before they run. Claude Desktop shows each tool call and asks for confirmation before executing. Review before you approve.
Use coach-scoped API keys for sensitive bulk actions. That way the AI can only touch clients assigned to a specific coach.
Create read-only API keys for analytics. When you only want to ask questions, give the AI a key with no write tools enabled.
