ACWR Analyzer Connector for AI agents.
4 live capabilities
Predict athlete injury risk by analyzing training load patterns.
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Why people use ACWR Analyzer
ACWR Analyzer Injury Prevention for Sports Science
With this Connector, you just feed the raw numbers to your agent. It does the math instantly, flags the danger zones, and tells you exactly what to do next. You get a clear Safe or Danger status in seconds, letting you spend less time on a spreadsheet and more time on the field.
What Vinkius changes
You get a clear, data-backed plan to keep your athletes safe and performing at their peak.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Soccer Team Injury Prevention
A coach notices a defender's load is spiking.
- Real-world use case 02
Marathon Training Analysis
A runner wants to know if their last three weeks were too intense.
- Real-world use case 03
Identifying Under-training
A swimmer's load drops too low.
Complete set · 4capabilities
The complete ACWR Analyzer capability set.
These are the exact actions your AI can choose when you ask it to work with ACWR Analyzer.
01—04
4 capabilities in this set.
Part of 4 available through ACWR Analyzer.
- 01 Capability
Calculate acwr series
Calculates a series of ACWR values to show how load ratios change over time. This helps you see the progression of training stress.
- 02 Capability
Evaluate risk tier
Places an athlete into a specific risk category like Safe, Warning, or Danger. This makes it easy to prioritize your attention.
- 03 Capability
Generate training prescription
Provides actionable coaching advice to adjust training based on detected risks. It gives you a clear plan for what to do next.
- 04 Capability
Detect load trend
Identifies whether a training load is increasing, decreasing, or staying stable. Use this to catch creeping intensity early.
Set up in minutes
One URL. Then ask ACWR Analyzer to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use ACWR Analyzer from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_6wJPlJEEtkpKouxdrtkiIYI1VteE0uLwqMkHkJ3C/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it ACWR Analyzer, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable ACWR Analyzer for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_6wJPlJEEtkpKouxdrtkiIYI1VteE0uLwqMkHkJ3C/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the ACWR Analyzer URL.
- Step 03
Save and start
Save the connection and enable ACWR Analyzer in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"acutechronic-workload-ratio-acwr-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_6wJPlJEEtkpKouxdrtkiIYI1VteE0uLwqMkHkJ3C/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using ACWR Analyzer
Open Agent mode in chat and ask: "Using ACWR Analyzer, help me...". 4 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"acutechronic-workload-ratio-acwr-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_6wJPlJEEtkpKouxdrtkiIYI1VteE0uLwqMkHkJ3C/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using ACWR Analyzer
Ask Copilot: "Using ACWR Analyzer, help me...". 4 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"acutechronic-workload-ratio-acwr-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_6wJPlJEEtkpKouxdrtkiIYI1VteE0uLwqMkHkJ3C/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using ACWR Analyzer
Open Cascade and ask: "Using ACWR Analyzer, help me...". 4 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"acutechronic-workload-ratio-acwr-analyzer": {
"url": "https://edge.vinkius.com/vk_preview_6wJPlJEEtkpKouxdrtkiIYI1VteE0uLwqMkHkJ3C/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using ACWR Analyzer
Ask Cline: "Using ACWR Analyzer, help me...". 4 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add acutechronic-workload-ratio-acwr-analyzer --transport http "https://edge.vinkius.com/vk_preview_6wJPlJEEtkpKouxdrtkiIYI1VteE0uLwqMkHkJ3C/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using ACWR Analyzer
Ask Claude: "Using ACWR Analyzer, show me...". 4 tools are ready
Where the request belongs
Work ACWR Analyzer can move forward.
This is for sports scientists and high-performance coaches who are tired of manually crunching spreadsheets to find injury risks and manage athlete workloads.
Sports Scientist
Analyzes weekly load data to create safe periodization plans and identify high-risk athletes.
Strength and Conditioning Coach
Adjusts daily workouts based on real-time stress levels to keep players healthy.
Team Performance Director
Monitors an entire roster's readiness to minimize time lost to non-contact injuries.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse Connectors
Perceived Exertion Converter
Convert RPE (Borg 6-20 and CR10) to estimated heart rate and training zones.
Lactate Threshold Estimator
Estimate metabolic lactate thresholds using effort-based metrics or heart rate drift analysis.
Heart Rate Zone Calculator
Calculate personalized training zones using the Karvonen formula and sport-specific adjustments.
Deload Calculator
Calculate precise training deload protocols based on accumulated fatigue and athletic discipline.
Recovery Readiness Score
Evaluate training readiness and optimal intensity based on sleep, soreness, stress, and motivation.
Training Load Calculator
Quantify training stress, detect overtraining risks, and generate recovery strategies.
Bring your own AI
Change the model, client or framework. Keep ACWR Analyzer connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about ACWR Analyzer.
The practical details behind the request, access and result.
How does the ACWR Analyzer help with injury prevention?
It identifies when an athlete's recent training load is spiking too fast compared to their long-term baseline. By flagging these 'Danger Zones,' it helps you catch potential injuries before they happen.
Can I use the ACWR Analyzer for individual athletes or teams?
Yes, it works for both. You can use it to monitor a single marathoner's training progress or scan an entire soccer roster to see who needs a workload adjustment.
What kind of data do I need to provide to the ACWR Analyzer?
You can provide any metric that represents training load, such as weekly mileage, total volume, intensity scores, or GPS-derived data points.
How does the training prescription work for my athletes?
The Connector looks at the current risk level and trend, then generates specific coaching advice. It tells you exactly how to adjust the next few days of training to stay safe.
Can it tell me if an athlete is under-training?
Yes, it identifies 'Under-training' zones. If an athlete's load drops too low, the Connector flags it so you can increase their volume and maintain their fitness.
Is the ACWR Analyzer for professional sports only?
It's for anyone who tracks training data. Whether you're a pro coach, a high school trainer, or a dedicated hobbyist, it provides the same sports science logic.
What is the purpose of the `calculate_acwr_series` capability?
It processes a sequence of weekly training loads to generate a series of ACWR values and summary statistics.
How does `evaluate_risk_tier` determine injury risk?
It applies specific thresholds to the current ratio: below 0.8 is Under-training, 0.8-1.3 is Safe, 1.3-1.5 is Moderate Risk, and above 1.5 is the Danger Zone.
Can I get coaching advice using this server?
Yes, the generate_training_prescription capability provides actionable instructions like 'Maintain', 'Increase', or 'Reduce' load based on your current ratio and trend.
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