TIMI Score Calculator MCP for AI. Turn raw patient data into an immediate care plan.
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The TIMI Score Calculator uses clinical inputs to generate accurate risk profiles for acute coronary syndrome (ACS). It calculates raw scores for STEMI and NSTEMI, estimates 14-day adverse event probability based on age, and provides immediate management recommendations following established guidelines.
What your AI can do
Derive adverse event risk
Takes a TIMI score and the patient's age to estimate their specific 14-day probability of an adverse cardiac event.
Recommend management strategy
Generates an immediate, authoritative course of action based on the final calculated risk category and MI type according to current guidelines.
Calculate timi score
Calculates TIMI risk scores for STEMI and NSTEMI using core clinical variables like age and ECG findings.
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TIMI Score Calculator: 3 Tools
These tools allow you to run a full, sequential clinical workflow: from initial score calculation to final treatment recommendation.
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 TIMI Score Calculator for ACS Risk Stratification on VinkiusDerive Adverse Event Risk
Takes a TIMI score and the patient's age to estimate their specific 14-day probability of an adverse cardiac event.
Recommend Management Strategy
Generates an immediate, authoritative course of action based on the final calculated...
Calculate Timi Score
Calculates TIMI risk scores for STEMI and NSTEMI using core clinical variables like...
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Claude AI
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Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
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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 connection provides 3 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The Manual Process of Risk Assessment
Right now, figuring out a patient's true risk involves pulling up multiple scorecards, cross-referencing lab values with age brackets, and manually checking protocols. You spend time copying numbers from one section of the chart into another calculator, then having to interpret that final number against dozens of guidelines.
With this MCP, you provide the initial data once. The agent runs the complex cascade in the background—calculating scores, estimating 14-day risk, and mapping it all to a clear recommendation. You get an instant, consolidated pathway for care.
Getting Guideline-Backed Decisions with `recommend_management_strategy`
You eliminate the need to manually verify if your recommended action (e.g., observation vs. angiography) matches the latest guidelines for a given risk category and MI type. The MCP handles that lookup instantly.
The final output isn't just a suggestion; it’s an actionable, evidence-based path derived from authoritative protocols. It changes how fast you can move from diagnosis to definitive care.
What your AI can actually do with this
When a patient presents with signs of acute coronary syndrome, the clock is ticking. You need to translate complex clinical data—age, ECG findings, lab results—into an actionable risk score immediately. This MCP guides you through that process by running interconnected calculations. It first generates separate TIMI scores for both STEMI and NSTEMI presentations using core variables.
Next, it maps those raw scores against the patient's age to estimate a concrete 14-day probability of adverse cardiac events. Finally, it synthesizes everything into an immediate management recommendation, citing guideline justification. Because this tool handles such high-stakes data, every single input and output is recorded in a cryptographically signed audit trail by Vinkius, ensuring the full history remains tamper-proof for your records.
You simply connect once from any compatible client to run this entire diagnostic cascade without leaving your workspace.
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Here's how it actually works
The bottom line is that you feed in raw patient data once and get a comprehensive, guideline-backed treatment pathway back.
Input core patient variables: you provide age, ECG findings, and prior CAD history.
The system first calculates the initial TIMI scores for both STEMI and NSTEMI using calculate_timi_score, then passes that result to estimate the 14-day risk via derive_adverse_event_risk.
Finally, it uses the resulting high-level risk category and MI type to output a definitive management plan through recommend_management_strategy.
Who is this actually for?
Emergency physicians and cardiologists who spend hours manually cross-referencing charts and scorecards. This MCP cuts through the noise, giving you an instant, reliable risk assessment when time is critical.
Running a patient into the ER after symptoms appear, needing to quickly determine if immediate angiography or observation is required.
Handling complex cases and needing to validate their initial risk score against established ACC/AHA guidelines before consulting with an attending physician.
Reviewing a high volume of patient charts post-event to ensure all necessary follow-up protocols were followed based on the calculated adverse event risk.
What Changes When You Connect
Instead of manually calculating scores, the system runs calculate_timi_score to instantly generate both STEMI and NSTEMI risk markers.
You get a quantitative measure of future danger. By using derive_adverse_event_risk, you translate raw numbers into a clear 14-day adverse event probability.
It connects the dots for you. The final step, running through recommend_management_strategy, ensures your advice aligns with current ACC/AHA guidelines.
The entire process is auditable and secure. Every tool call records its inputs and outputs in a cryptographically signed audit trail.
You don't have to switch systems. Your agent handles the full cascade—from initial score calculation to final recommendation—all from one place.
See it in action
Acute STEMI Triage
A resident gets a patient in with ST elevation. They call calculate_timi_score for the initial score, then feed that result and age into derive_adverse_event_risk. Finally, they send both outputs to recommend_management_strategy to confirm immediate angiography is the correct next step.
NSTEMI Follow-up Assessment
A physician needs to reassess a stable patient with NSTEMI. They use calculate_timi_score, get a score, and then pass that result into derive_adverse_event_risk to confirm if the 14-day risk has dropped below acceptable thresholds.
Protocol Confirmation
A clinician is reviewing guidelines for an elderly patient. They use recommend_management_strategy, providing a high risk category and NSTEMI type, forcing the MCP to cite the specific guideline justification needed for sign-off.
Multi-Stage Patient Intake
The agent runs a full chain: first calculate_timi_score, then uses that score in derive_adverse_event_risk to establish risk, and finally feeds the risk into recommend_management_strategy for one single, definitive output.
The honest tradeoffs
Checking scores in isolation
Just calling calculate_timi_score and stopping there. You get a score, but you don't know what that means for the patient over two weeks.
You must chain the tools: first use calculate_timi_score, then pass its output to derive_adverse_event_risk. Only after confirming the 14-day risk should you call recommend_management_strategy.
Ignoring age factors
Manually calculating a score and writing off the recommendation without considering how the patient's advanced age changes the prognosis.
Always include the patient’s age in the workflow. derive_adverse_event_risk specifically uses age to adjust the final probability, ensuring your advice is holistic.
Using vague criteria
Writing 'The patient needs treatment' instead of citing the specific guideline that mandates it.
Always let recommend_management_strategy handle the final step. It guarantees the output is tied back to specific, authoritative ACC/AHA guidelines.
When It Fits, When It Doesn't
Use this MCP if your task requires synthesizing multiple clinical data points into a single, mandated action plan based on established protocols. This tool excels when you need to move from raw data (age, ECG findings) through an intermediate calculation (14-day risk probability) and end with a definitive decision. Don't use it if you just need to check one single metric, like blood pressure or basic vitals; those tools are simpler. Also, don't rely on this for diagnosing the initial condition—it only predicts risk after an ACS event is suspected. You still need human expertise to interpret the results and manage edge cases.
Questions you might have
How does the TIMI Score Calculator for ACS Risk Stratification work? +
It works by creating a three-step workflow: first, it uses calculate_timi_score to get baseline numbers; second, it runs those scores through derive_adverse_event_risk using age; and finally, it gives you the protocol with recommend_management_strategy.
Can I use calculate_timi_score alone? +
You can, but you'll only get a raw score. For full clinical value, always follow up by using that output in derive_adverse_event_risk and then passing the result to recommend_management_strategy.
What is the difference between TIMI score and adverse event risk? +
The TIMI score is a baseline marker of severity. The MCP uses derive_adverse_event_risk to translate that raw score, adjusting it for age, into a much more practical 14-day probability.
Does the recommendation MCP cite guidelines? +
Yes. When you run recommend_management_strategy, the output is explicitly tied to current ACC/AHA guidelines, providing immediate justification for the suggested care path.
When I run `calculate_timi_score`, how does Vinkius handle the sensitive patient data? +
Your credentials pass through a zero-trust proxy, keeping them safe. They're only used in transit and never stored on disk, ensuring your keys stay private.
What kind of AI client can I connect to use `derive_adverse_event_risk`? +
You just need an MCP-compatible client. Whether you're using Claude, Cursor, Windsurf, or VS Code, connecting your agent once gives you access to this tool.
If I provide bad inputs to `recommend_management_strategy`, how does the system handle it? +
The MCP validates the data structure first. If something's wrong with your input, you get a clear error message that tells you exactly which field needs fixing.
Does Vinkius optimize token usage when I chain tools starting from `calculate_timi_score`? +
Yes. Every MCP call includes native token optimization built in. This cuts down on your token consumption by up to 60% compared to running the same sequence without it.
What inputs are required to calculate the initial TIMI score? +
The calculate_timi_score tool requires patient age, key ECG abnormalities (ecgFindings), and whether the patient has a history of Coronary Artery Disease (priorCADHistory). Creatinine level is optional.
Does the calculated score determine the management strategy directly? +
No. First, you use derive_adverse_event_risk to get a probability estimate. Then, recommend_management_strategy takes that risk category and the MI type (STEMI/NSTEMI) to provide the final guideline recommendation.
Can I calculate scores for different types of MIs? +
Yes. The calculate_timi_score tool is designed to run two separate calculations, providing distinct provisional scores tailored specifically for STEMI and NSTEMI presentations.
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