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The Motiva Metrics MCP server connects the assistant you already use - Claude, an internal Slack bot, your own agent - straight to your measurement. The answer arrives as a sentence, with no charts or reports to read.
The minimum of five respondents applies to the assistant exactly as it does to you.
Where is our engagement problem?
get_measurement · get_breakdown
Engineering - a score of 47 (58 across the whole organisation). The cause is career development - a score of 29, the lowest figure in the measurement, and the strongest predictor of turnover intention in this dataset.
What is the agenda for the career paths initiative?
get_action_plan · get_artifacts
It ships with the initiative. Three items: map the levels that already exist informally, agree the criteria with the team leads, then one conversation per person inside the quarter.
MCP server
Your Motiva Metrics measurement, inside the assistant you already use.
Model Context Protocol is the open standard for giving an AI assistant read access to a system. So this is not a chatbot bolted onto our own dashboard - it is your assistant, with your data.
Three steps, and it is done
- 01
You get a key
Read-only, scoped to your organisation, revocable at any moment.
- 02
You paste it in
Into Claude, into Claude Code, into an internal Slack bot, into whatever agent your company already runs.
- 03
You ask
In your own words, in Serbian or English. The assistant reads your measurement and answers from it - and says so when the data does not answer.
Ask your data
Through the MCP server
Which department is costing us the most, and why?
Engineering. Satisfaction with career development there is only 29, and engagement 47. Career development is also the strongest predictor of turnover intention in this dataset, and Engineering has the highest turnover intention of any department.
What is overdue right now?
One initiative: “A decision is announced before it takes effect”. Owner Nikola P., due 15 March 2026, 1 of 4 steps done.
Every figure comes from your own measurement, through the MCP server. If it is not in the data, the assistant says so rather than filling the gap.
What can you ask it?
It connects the data and gives answers grounded in Motiva Metrics.
- CEO
“Which department is costing us the most, and why?”
measurement · cost model
- HR lead
“Compare this measurement with the last one and tell me what moved.”
measurement · trend
- HR lead
“What is overdue in the action plan, and who owns it?”
action plan · implementation
- Manager
“Draft Monday's agenda for the career paths initiative.”
action plan · artefacts
- Manager
“My team scored low on change management. What does the report say to do?”
report
- CFO
“If career development moves ten points, what happens to the cost?”
cost model · simulation
What it can read
- Every metric and predictor, with breakdowns for groups of five or more employees
- The written report, section by section
- The action plan: initiatives, steps, owners and deadlines
- Implementation status, including what is overdue
What it can never do
- Write, change or delete anything.
- Reach an individual answer.
- Break the five-respondent floor.
- Reach another organisation's data.
AI in the platform
And this part has been working all along.
An advanced AI model is given all the data it needs and analyses it with high accuracy, using the Motiva Metrics methodology.
01
The report is written from your data
When a measurement closes, the AI model is given all the data it needs: every metric and every predictor with its measured value, the predictive models, and the methodology already in the system.
- An advanced AI model, run at high reasoning effort
- A report for the whole measurement
- Written in Serbian or English
- Tailored to your industry
- Key themes mapped for the work ahead
Report
Built from this measurement
Burnout
AverageMotivational pattern: autonomous motivation holds, but Operations is carrying the strain
- Current state
- Burnout is moderate (41) across the organisation, but it is not evenly spread. It is highest in Operations (54) and lowest in Support (31).
- Why this is happening
- In Operations, high burnout coincides with the lowest satisfaction with managers (45) and with change management (36). People carry a heavy workload without enough support, and hear about changes too late to prepare. Autonomous motivation still holds, so this is not a loss of will but exhaustion that can be reduced.
- What needs to be done
- With the team leads in Operations, review how work and priorities are spread, introduce short weekly conversations about workload, and agree rules on overtime and availability outside working hours. October's measurement will show whether it moved.
- Satisfaction with career development38Poor
- Satisfaction with change management42Poor
- Satisfaction with colleagues74Good
Downloads as a Word document.
02
Your data picks the initiatives. The AI writes them up.
Which initiatives you are given is decided before the model is ever called: the system selects them using scientifically grounded, validated predictive models that it tests against your data. The model is handed the recommendations your measurement has already activated, and writes the rationale, the steps, the expected outcome and the risk of doing nothing - together with every agenda, checklist, survey and template needed to run them.
- Initiatives selected from your data and the predictive models in the system
- The AI writes the reasoning; it does not choose the recommendation
- Every initiative worked out in detail
- Rationale, steps, outcome, minimum viable version, risk of doing nothing
Action plan
Generated from this measurement
Phase 1 - first ninety days
Reduce workload and build in recovery in Operations
Burnout scores 41 overall and 54 in Operations - the highest in the organisation, alongside the lowest satisfaction with managers (45) in the same department.
Steps
Review workload and priorities with the team leads
Introduce short weekly conversations about workload
Agree rules on overtime and availability outside working hours
Risk of not doing it: Operations already shows the highest burnout. Without relief, exhaustion turns into absence and departures, and the first to go are the people the work rests on most.
A decision is announced before it takes effect
Change management scores 42, and 36 in Operations. People are not resisting the changes - they are finding out about them too late to prepare.
Phase 2 - months four to nine
Manager support programme for Operations
Manager satisfaction is 45 in Operations against 71 in Sales. The gap is not about people; it is about which managers have ever been taught to do this part of the job.
Regular one-to-ones with a written agenda
The cheapest intervention in the plan, and the one with the broadest effect: it moves autonomy, competence and relatedness at the same time.
03
What the AI receives from the data
Generating the documents is the only step that reaches our model at all, and what it is given is a fixed export: the measured value of each metric, the results of every defined predictive model, your company name, the measurement period, and your industry and size.
- Company-level values only
- No names, no email addresses, no login data
- No individual results
- Nothing is used to train a model
- Generation is a deliberate step someone runs
Get connected
Put your Motiva Metrics data in your own assistant.
Tell us who should have a key and we will set it up with you - which assistant you want it in, and whether you want a key for the whole organisation or for a particular department.
Not a client yet? This is also the fastest way to see what the MCP server can do, on demo data.
Frequently asked questions
Find out what really drives your people
Book a 30-minute demo and find out how Motiva Metrics can help you.