Mood Pattern Detector Connector for AI agents.
3 live capabilities
Track emotional trends and lifestyle correlations to improve your daily well-being.
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Why people use Mood Pattern Detector
Mood Pattern Detector for lifestyle analytics and trend spotting
This Connector changes that by doing the math for you. It scans your history and pulls out the actual correlations. Instead of scrolling, you just ask your agent for the facts and get a clear picture of how your habits shape your headspace.
What Vinkius changes
You get a data-driven look at how your life actually affects your mood.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Checking sleep impact
A user wants to know if staying up late ruins their mood.
- Real-world use case 02
Coaching client progress
A coach wants to see if a client's mood improves on days they hit the gym.
- Real-world use case 03
Finding weekly slumps
A person wants to know why they feel off every Wednesday.
Complete set · 3capabilities
The complete Mood Pattern Detector capability set.
These are the exact actions your AI can choose when you ask it to work with Mood Pattern Detector.
01—03
3 capabilities in this set.
Part of 3 available through Mood Pattern Detector.
- 01 Capability
Identify mood anomalies
This capability finds specific dates where your mood jumped or dropped way outside your normal range. It flags significant deviations.
- 02 Capability
Analyze weekly cycle
This capability shows which days of the week consistently make you feel better or worse. It helps you identify recurring weekly drags.
- 03 Capability
Evaluate activity impact
This capability checks if things like exercise or sleep changes actually move the needle on your mood. It measures specific variable impacts.
Set up in minutes
One URL. Then ask Mood Pattern Detector to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Mood Pattern Detector 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_ZCuceq86hBITNbpAViGII3gpOVbb3AwuDqYgNjUi/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 Mood Pattern Detector, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Mood Pattern Detector for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ZCuceq86hBITNbpAViGII3gpOVbb3AwuDqYgNjUi/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 Mood Pattern Detector URL.
- Step 03
Save and start
Save the connection and enable Mood Pattern Detector in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"mood-pattern-detector": {
"url": "https://edge.vinkius.com/vk_preview_ZCuceq86hBITNbpAViGII3gpOVbb3AwuDqYgNjUi/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 Mood Pattern Detector
Open Agent mode in chat and ask: "Using Mood Pattern Detector, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"mood-pattern-detector": {
"url": "https://edge.vinkius.com/vk_preview_ZCuceq86hBITNbpAViGII3gpOVbb3AwuDqYgNjUi/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 Mood Pattern Detector
Ask Copilot: "Using Mood Pattern Detector, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"mood-pattern-detector": {
"url": "https://edge.vinkius.com/vk_preview_ZCuceq86hBITNbpAViGII3gpOVbb3AwuDqYgNjUi/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 Mood Pattern Detector
Open Cascade and ask: "Using Mood Pattern Detector, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"mood-pattern-detector": {
"url": "https://edge.vinkius.com/vk_preview_ZCuceq86hBITNbpAViGII3gpOVbb3AwuDqYgNjUi/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 Mood Pattern Detector
Ask Cline: "Using Mood Pattern Detector, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add mood-pattern-detector --transport http "https://edge.vinkius.com/vk_preview_ZCuceq86hBITNbpAViGII3gpOVbb3AwuDqYgNjUi/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 Mood Pattern Detector
Ask Claude: "Using Mood Pattern Detector, show me...". 3 tools are ready
Where the request belongs
Work Mood Pattern Detector can move forward.
This is for people who want to move beyond feeling and start knowing. It's for the wellness coach who needs objective evidence for a client, the productivity hacker looking for a slump, or the individual trying to see if their lifestyle changes actually work.
Wellness Coach
Use it to find objective trends for clients who struggle to articulate their feelings or identify lifestyle triggers.
Productivity Hacker
Identify the specific days or habits that cause brain fog or energy slumps to optimize your work week.
Habit Tracker
See if your new routines are actually improving your mental well-being by checking the data.
Data Enthusiast
Turn personal sentiment logs into structured lifestyle analytics to better understand your emotional baseline.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse Connectors
Mood Tracker
Analyze daily mood logs to identify emotional trends and weekly patterns.
Emotional Variability Score
Quantify emotional fluctuations, mood amplitude, and longitudinal stability.
Mood & Productivity Correlator
Analyze the statistical relationship between your mood, lifestyle habits, and daily productivity levels.
Anxiety Management Tracker
Track anxiety patterns, identify triggers, and evaluate coping strategy effectiveness.
Emotion Wheel Classifier
Map raw text descriptions to Plutchik's Wheel of Emotions, identifying intensity and emotional families.
Burnout Detector
Assess burnout risk using the Maslach Burnout Inventory (MBI) model.
Bring your own AI
Change the model, client or framework. Keep Mood Pattern Detector connected.
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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 Mood Pattern Detector.
The practical details behind the request, access and result.
How does Mood Pattern Detector help with my mental health?
It helps you identify objective patterns in your emotions. By connecting your mood logs to lifestyle data, it shows you the actual correlations between your habits and your feelings.
Can Mood Pattern Detector find my mood triggers?
Yes. It looks for correlations between variables like sleep, exercise, and work hours to see what specifically impacts your mood levels.
How do I use Mood Pattern Detector to see my sleep impact?
You can ask your agent to evaluate the impact of sleep. The capability will compare your mood scores on high-sleep days versus low-sleep days to give you a clear average.
What kind of data does Mood Pattern Detector analyze?
It analyzes your historical mood entries and compares them against various lifestyle variables you've recorded, such as activity, sleep, and daily cycles.
Can Mood Pattern Detector find my weekly patterns?
Yes, it can identify if specific days of the week are consistently associated with better or worse moods, helping you spot recurring weekly trends.
Is Mood Pattern Detector good for habit tracking?
It's perfect for habit tracking because it tells you if your habits are actually working. It moves you from just tracking a habit to seeing the results of that habit on your well-being.
How does the detector identify weekly patterns?
The analyze_weekly_pattern capability calculates the average mood score for each day of the week present in your logs and identifies significant differences between days.
Can I analyze specific activities like exercise or sleep?
Yes, using evaluate_activity_impact, you can provide the name of any recorded variable to see its correlation with your mood levels.
What constitutes a mood anomaly?
An anomaly is flagged by identify_mood_anomalies when a specific day's mood score deviates from your historical baseline beyond a defined sensitivity threshold.
One connection away
Give your agent a direct line to Mood Pattern Detector.
Connect Mood Pattern Detector once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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