# Heart Score Calculator MCP

> Heart Score Calculator determines acute myocardial infarction (AMI) risk by synthesizing five key clinical metrics: History, ECG findings, Age, Risk Factors, and Troponin levels. This MCP provides immediate, guideline-backed scoring and triage recommendations for chest pain patients.

## Overview
- **Category:** cardiology
- **Price:** Free
- **Tags:** heart-score, ami, ecg, troponin, triage

## Description

When a patient presents with chest pain, doctors need more than just gut feelings; they need an objective risk score. This MCP takes the complex clinical data—history, ECG readings, comorbidities, and troponin levels—and structures it into a single, actionable assessment. Instead of spending time cross-referencing multiple hospital protocols or manually calculating scores across different sheets, your AI client handles the heavy lifting. It first calculates a total HEART score from all five inputs. Next, it instantly maps that number to a specific risk category and defined triage priority. Finally, it generates mandatory diagnostic pathways, telling care teams exactly which tests to order and how the patient needs to be managed immediately. You'll connect this MCP via Vinkius, giving your agents instant access to standardized clinical decision support.

## Tools

### calculate_heart_score
Combines history, ECG, age, risk factor, and troponin data to provide a total HEART score for AMI assessment.

### classify_risk_and_triage
Takes the calculated heart score and assigns an official 'Low', 'Moderate', or 'High' risk status along with a triage level.

### recommend_clinical_conduct
Generates specific, evidence-based medical recommendations for tests, management, and follow-up based on the final risk classification.

## Prompt Examples

**Prompt:** 
```
Patient profile: Age 68, History score 2 (Anginal at rest), ECG score 1 (T-wave inversion), Risk Factor score 2 (Diabetes/Hypertension). Troponin is mildly elevated. Calculate the HEART score and recommend initial conduct.
```

**Response:** 
```
First, I will use `calculate_heart_score` with inputs: historyScore=2, ecgFindingsScore=1, ageFactorScore=2, riskFactorComorbidityScore=2, troponinSeverityScore=1. The total score is 8. Next, using `classify_risk_and_triage(totalScore=8)`, the result is 'High Risk' with Triage Level 3. Finally, I call `recommend_clinical_conduct('High Risk')` which mandates immediate admission and urgent investigation.
```

**Prompt:** 
```
I have a young patient (Age 35) with minimal symptoms. My calculated HEART score is 2. What should the next steps be?
```

**Response:** 
```
The `classify_risk_and_triage` tool confirms a 'Low Risk' status for a total score of 2. Therefore, I run `recommend_clinical_conduct('Low Risk', false)` to get the recommended pathway. The output will guide us toward outpatient follow-up and discharge protocols.
```

**Prompt:** 
```
Run a full assessment for an 85-year-old male presenting in the ER. Scores are: History=1, ECG=0, Age=2, RF=1, Troponin=0.
```

**Response:** 
```
Initial calculation via `calculate_heart_score` yields a total score of 4. Using the `classify_risk_and_triage(totalScore=4, patientAgeGroup='over 80')` tool confirms 'Moderate Risk' with Triage Level 2. I then use `recommend_clinical_conduct('Moderate Risk', true, true)` to get actionable ER guidelines.
```

## Capabilities

### Calculate total HEART score
Aggregates five separate clinical metrics (History, ECG, Age, Risk Factor, Troponin) into a single numerical risk score.

### Assign risk category and triage level
Takes the final calculated HEART score and determines if the patient is Low, Moderate, or High risk, assigning an immediate triage priority.

### Generate clinical management pathways
Creates evidence-based next steps, including mandatory diagnostic tests and follow-up protocols, based on the assigned risk level.

## Use Cases

### Triage a suspected AMI in the ER
An incoming patient has chest pain. Instead of starting from scratch, your agent first runs `calculate_heart_score` using all available data. It gets a total score and immediately passes it to `classify_risk_and_triage`, which assigns 'High Risk' with Triage Level 3. This triggers the final step: calling `recommend_clinical_conduct('High Risk')` to mandate immediate admission protocols.

### Follow up on a stable, low-score patient
A young patient is admitted with minimal symptoms and a calculated HEART score of 2. The agent uses `classify_risk_and_triage` to confirm 'Low Risk'. Then, it calls `recommend_clinical_conduct('Low Risk')`, which guides the care team toward safe outpatient follow-up rather than unnecessary imaging.

### Reviewing complex comorbidities
Assessing an 85-year-old male with multiple risk factors. The agent calculates the score, confirming 'Moderate Risk'. It then uses `recommend_clinical_conduct` to get a specific ER guideline that adjusts for age and gender, ensuring the care plan is highly customized.

### Validating initial assessment findings
A physician manually calculates a score but wants confirmation. The agent runs `calculate_heart_score` to validate the inputs. It then uses `classify_risk_and_triage` to confirm the risk tier before running `recommend_clinical_conduct('Moderate Risk')` for final sign-off.

## Benefits

- Eliminate manual score calculation. The `calculate_heart_score` tool aggregates all five necessary components, giving you a single number instead of juggling multiple data inputs.
- Ensure consistent patient care. The system doesn't just give advice; it uses `classify_risk_and_triage` to map the score directly to mandatory Low, Moderate, or High risk tiers, standardizing triage across shifts.
- Get actionable next steps immediately. Instead of generic guidelines, `recommend_clinical_conduct` outputs a specific list of required tests and management directives for your care team.
- Focus on diagnosis, not documentation. By automating the complex synthesis process, clinicians can dedicate their attention to patient care rather than cross-referencing multiple clinical pathways.
- Reduce assessment variability. The MCP enforces adherence to AHA/ESC guidelines, ensuring every patient receives an objective score and protocol regardless of who is assessing them.

## How It Works

The bottom line is: your AI client converts scattered clinical data points into an immediate, clear action plan.

1. Feed the necessary patient data (History score, ECG findings, Age group, Risk Factor status, Troponin severity) into the system.
2. The MCP uses `calculate_heart_score` to combine these metrics and produce a total risk number from 0 to 10.
3. It then runs this total score through `classify_risk_and_triage` to assign a definitive risk level, followed by calling `recommend_clinical_conduct` for specific care directives.

## Frequently Asked Questions

**How does Heart Score Calculator MCP determine if the patient needs immediate admission?**
The system uses `classify_risk_and_triage` first to assign 'High Risk' status. Then, calling `recommend_clinical_conduct('High Risk')` generates mandatory directives for immediate inpatient admission and urgent investigation.

**Does Heart Score Calculator MCP work if I only have ECG data?**
The tool can calculate a score even with missing information, as many inputs are optional. However, the resulting recommendation will be less definitive without full history and troponin details.

**What is the difference between `classify_risk_and_triage` and `recommend_clinical_conduct`?**
`classify_risk_and_triage` only provides a risk label (Low/Moderate/High) and a Triage Level. You must then use `recommend_clinical_conduct` to get the actual, detailed medical actions required.

**Can Heart Score Calculator MCP run an assessment for someone over 80?**
Yes. The scoring tools are designed to take age groups into account when calculating risk and generating clinical recommendations, ensuring the care plan is tailored to the patient's demographic.

**What type of data does calculate_heart_score need?**
It requires five components: History score, ECG findings score, Age factor score, Risk Factor status, and Troponin severity. Missing inputs simply default the component score to zero.