Heart Score Calculator MCP. Automate AMI Risk Assessment from Symptoms to Action Plan
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Heart Score Calculator determines a patient's risk of acute myocardial infarction (AMI) by analyzing five key clinical metrics. This MCP takes inputs like history scores, ECG findings, age factors, comorbidities, and troponin levels to generate a total score.
It then classifies the resulting risk into Low, Moderate, or High categories, delivering mandatory diagnostic pathways and specific next steps for immediate care.
What your AI agents can do
Calculate heart score
Calculates the total HEART score, combining history, ECG, age, risk factors, and troponin levels into a single metric.
Classify risk and triage
Takes the resulting heart score to assign an official risk category (Low/Moderate/High) and determine the required triage level.
Recommend clinical conduct
Generates mandatory, evidence-based clinical guidelines, specifying tests and management based on the final risk classification.
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Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Heart Score Calculator: 3 Tools
Use these three tools sequentially to calculate a total risk score, classify the patient's severity, and generate specific clinical recommendations.
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Start using Heart Score Calculator on Vinkius019ecb73calculate heart score
Calculates the total HEART score, combining history, ECG, age, risk factors, and troponin levels into a single metric.
019ecb73classify risk and triage
Takes the resulting heart score to assign an official risk category (Low/Moderate/High) and determine the required triage level.
019ecb73recommend clinical conduct
Generates mandatory, evidence-based clinical guidelines, specifying tests and management based on the final risk classification.
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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 server provides 3 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Handling initial cardiac assessments used to be a mess of protocols and forms.
Today, a chest pain assessment means gathering data from multiple sources—charting history, reading ECG printouts, checking lab values, and cross-referencing those against different clinical guidelines. The process is prone to human variability; it's easy to miss an input or misinterpret which protocol applies based on age group alone.
With this MCP, the entire assessment runs through a single agent workflow. You feed in the initial data points, and the system manages the sequence: calculating the score, assigning the risk category, and then generating the full care plan. You get an immediate, actionable pathway designed for high-stakes clinical environments.
The Heart Score Calculator MCP delivers clear diagnostic paths.
You don't have to manually check if the score is low enough to rule out intervention. The workflow handles this automatically. Running `classify_risk_and_triage` instantly tells you the priority level, and then `recommend_clinical_conduct` produces a list of required tests and management directives.
The result is an authoritative, guideline-backed output that minimizes diagnostic gaps. You stop wasting time cross-referencing protocol sheets; the next step is simply implementation.
What you can do with this MCP connector
Assessing chest pain requires synthesizing data from multiple sources—History, ECGs, Age, Risk Factors, and Troponin—to build an actionable risk score. This MCP automates that process. Instead of relying on manual calculation and interpretation against complex AHA/ESC guidelines, your agent runs the full assessment in sequence. First, it aggregates all five clinical components into a single total score.
Next, it maps that numerical score to a definitive risk category (Low, Moderate, or High). Finally, it generates mandatory diagnostic pathways specific to that risk level. The result isn't generic advice; it outputs clear next steps—which tests to order and where the patient needs immediate management. Because this entire assessment involves chaining multiple clinical decision points together, running these tools through Vinkius allows you to build reliable automated workflows that span complex medical logic, guaranteeing a traceable audit trail for every single calculation.
019ecb73-fd88-70c6-be6a-8c88fe6ca041 
How Heart Score Calculator MCP Works
- 1 Provide the initial clinical data—including history findings, ECG scores, age factors, risk factor comorbidities, and troponin levels. The agent uses this information to calculate a total HEART score.
- 2 Feed the resulting numerical score into the triage tool. This step determines if the patient falls into Low, Moderate, or High risk categories and assigns an immediate priority level.
- 3 The final risk classification is passed to the conduct recommendation tool. It generates mandatory diagnostic pathways, management directives, and follow-up schedules based on established medical standards.
The bottom line is that you get a complete, guided care pathway—from initial score calculation to specific next steps for the patient.
Who Is Heart Score Calculator MCP For?
Cardiology residents and attending physicians who are tired of juggling multiple clinical guidelines and manual risk calculations. This MCP gives your agent immediate confidence in triage decisions, letting you focus on high-priority care.
Uses the system to quickly assess incoming patients with chest pain, determining if they need immediate admission or can be safely discharged.
Runs the full assessment workflow to ensure all mandatory diagnostic pathways are followed, especially when inputs (like age group) might affect outcomes.
Relies on the risk classification output to prioritize patient flow and guide initial orders for testing.
What Changes When You Connect
- Moves beyond guesswork. Instead of just generating a score, using
classify_risk_and_triageimmediately maps that number to 'Low', 'Moderate', or 'High' risk status. - Provides actionable next steps. The final output from
recommend_clinical_conducttells you exactly which tests to order and where the patient should be managed. - Handles complexity automatically. It aggregates five different clinical metrics—H, E, A, R, T—in one go using
calculate_heart_score, eliminating manual summation errors. - Maintains compliance. The workflow adheres strictly to current AHA/ESC guidelines, ensuring every recommended action is backed by established medical standards.
- Reduces cognitive load. By chaining the tools sequentially, you eliminate the need to manually interpret a score and then cross-reference it with multiple clinical flow charts.
Real-World Use Cases
Initial ER Assessment for Chronic Patients
A 68-year-old patient arrives with chest pain. The agent first runs calculate_heart_score to get the total score (e.g., 8). It then calls classify_risk_and_triage('totalScore=8'), which flags 'High Risk'. Finally, running recommend_clinical_conduct('High Risk') mandates immediate admission and urgent investigation.
Follow-up for Low-Risk Discharges
A 35-year-old patient with minimal symptoms has a calculated score of 2. The agent uses classify_risk_and_triage(totalScore=2) to confirm 'Low Risk'. Running recommend_clinical_conduct('Low Risk') guides the team toward safe outpatient follow-up and discharge protocols.
Complex, Multi-Variable Cases
Assessing an 85-year-old male in the ER. The workflow must account for advanced age and specific comorbidities. Running calculate_heart_score followed by classify_risk_and_triage(totalScore=4, patientAgeGroup='over 80') provides a nuanced 'Moderate Risk' classification.
Protocol Verification
The physician needs to verify the correct protocol for an intermediate-risk patient. The agent runs calculate_heart_score, then uses classify_risk_and_triage to confirm a 'Moderate Risk' status, and finally calls recommend_clinical_conduct('Moderate Risk', true, false) to get specific ER guidelines.
The Tradeoffs
Only using one calculation tool
Just running the score calculation and stopping. You have a number (e.g., 5), but no idea what that means clinically.
→
You must chain the tools. First, run calculate_heart_score to get the total. Then, pass that result into classify_risk_and_triage, and finally use the resulting category in recommend_clinical_conduct. The sequence matters.
Ignoring patient context
Running a basic score calculation without providing age group or ER setting details, leading to potentially incorrect triage.
→
Always provide the full clinical context. When running calculate_heart_score, ensure you include all optional metrics like ageFactorScore and riskFactorComorbidityScore. The tools are designed for depth.
Treating the output as final
Accepting the recommendations without clinical review. This MCP is a decision support tool, not a replacement for human judgment.
→ Use this to generate the mandatory diagnostic pathway, but remember that all results must be validated by a clinician. The system provides the foundation; you provide the final sign-off.
When It Fits, When It Doesn't
Use this MCP if your primary need is structured, guideline-backed clinical decision support for acute cardiac assessment. If you have scores and metrics (History, ECG, Age, RF, Troponin) and you need a definitive path from score to action plan, this is the right toolset. Don't use it if you are trying to diagnose symptoms not related to AMI risk, or if you only need to calculate one single component of the score. If your goal is simply data aggregation without triage, a simpler data processing MCP might suffice; but for full clinical workflow, this combination of three tools is necessary.
Common Questions About Heart Score Calculator MCP
How does calculate_heart_score handle missing data? +
It handles optional inputs gracefully. If you don't provide a specific score, it defaults to zero for that component, allowing the calculation to proceed without interruption.
Can classify_risk_and_triage determine if I need an immediate ambulance? +
It determines triage priority based on the total score. The output from recommend_clinical_conduct will provide explicit guidance, such as mandatory admission or urgent investigation.
If I run recommend_clinical_conduct first, what happens? +
The system requires the risk classification to run first. You must pass the 'Low', 'Moderate', or 'High' status from classify_risk_and_triage into this tool for accurate recommendations.
Does Heart Score Calculator require all five clinical metrics? +
No, it doesn't. The tools are designed to accept partial data while still performing a calculated assessment and providing the best possible guidance based on what you provide.
When using calculate_heart_score, does it account for variations in regional medical guidelines? +
Yes. The tool adheres strictly to established AHA/ESC guidelines. It calculates the total score by aggregating inputs (H, E, A, R, T) according to internationally recognized clinical standards.
How do I verify that the final recommendations from recommend_clinical_conduct are untampered? +
Every tool call creates a cryptographically signed audit trail. This gives you an immutable record of every input and output used to generate the clinical conduct, guaranteeing data integrity.
If I provide inputs that result in an unusual score range, how does classify_risk_and_triage handle it? +
The tool validates your input scores against established medical norms. If the total score falls outside expected parameters, it flags a validation error and requires you to correct the data before classification can proceed.
What is the most accurate workflow when combining calculate_heart_score with other tools? +
Always run calculate_heart_score first. This step establishes the foundational total score, which must then be fed directly into classify_risk_and_triage to ensure an accurate and consistent assessment chain.
Use it with your favorite AI tools
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