Linear Regression Calculator Connector for AI agents.
3 live capabilities
Perform deterministic least-squares regression and volatility analysis
Waiting for input…
Why people use Linear Regression Calculator
Stop guessing trends with Linear Regression Calculator math
With this MCP, you stop guessing. You feed the raw numbers to your agent, and it performs actual least-squares regression. You get hard numbers—slopes, intercepts, and standard deviation boundaries—that don't change based on how the AI is feeling that day.
What Vinkius changes
You turn raw price lists into structured statistical models.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Verifying a breakout
A trader sees a price spike and asks their agent if the trend is real.
- Real-world use case 02
Setting stop-loss levels
An analyst needs to find where a price might bounce.
- Real-world use case 03
Predicting next-period prices
A developer provides a recent price series and asks for the next expected value.
Complete set · 3capabilities
The complete Linear Regression Calculator capability set.
These are the exact actions your AI can choose when you ask it to work with Linear Regression Calculator.
01—03
3 capabilities in this set.
Part of 3 available through Linear Regression Calculator.
- 01 Capability
Analyze trend strength
Evaluates how reliable a trend is by checking its statistical fit. This helps you avoid chasing weak or noisy price movements.
- 02 Capability
Calculate regression channels
Creates upper and lower price boundaries based on standard deviation. Use this to identify when prices are overextended.
- 03 Capability
Calculate regression line
Computes the core linear regression line including slope and intercept. It provides the mathematical foundation for trend projection.
Set up in minutes
One URL. Then ask Linear Regression Calculator to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Linear Regression Calculator 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_gkWWSWiMxEW5sqYBLRUMsKzhgpSFPhqF5Hv4e37A/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 Linear Regression Calculator, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Linear Regression Calculator for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_gkWWSWiMxEW5sqYBLRUMsKzhgpSFPhqF5Hv4e37A/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 Linear Regression Calculator URL.
- Step 03
Save and start
Save the connection and enable Linear Regression Calculator in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"linear-regression-calculator": {
"url": "https://edge.vinkius.com/vk_preview_gkWWSWiMxEW5sqYBLRUMsKzhgpSFPhqF5Hv4e37A/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 Linear Regression Calculator
Open Agent mode in chat and ask: "Using Linear Regression Calculator, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"linear-regression-calculator": {
"url": "https://edge.vinkius.com/vk_preview_gkWWSWiMxEW5sqYBLRUMsKzhgpSFPhqF5Hv4e37A/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 Linear Regression Calculator
Ask Copilot: "Using Linear Regression Calculator, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"linear-regression-calculator": {
"url": "https://edge.vinkius.com/vk_preview_gkWWSWiMxEW5sqYBLRUMsKzhgpSFPhqF5Hv4e37A/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 Linear Regression Calculator
Open Cascade and ask: "Using Linear Regression Calculator, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"linear-regression-calculator": {
"url": "https://edge.vinkius.com/vk_preview_gkWWSWiMxEW5sqYBLRUMsKzhgpSFPhqF5Hv4e37A/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 Linear Regression Calculator
Ask Cline: "Using Linear Regression Calculator, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add linear-regression-calculator --transport http "https://edge.vinkius.com/vk_preview_gkWWSWiMxEW5sqYBLRUMsKzhgpSFPhqF5Hv4e37A/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 Linear Regression Calculator
Ask Claude: "Using Linear Regression Calculator, show me...". 3 tools are ready
Where the request belongs
Work Linear Regression Calculator can move forward.
Quantitative traders and data-driven analysts who need to move past visual chart guessing and into hard math.
Quantitative Trader
Uses regression lines to identify mean reversion opportunities or trend strength.
Financial Analyst
Generates volatility channels to define support and resistance levels mathematically.
Algorithmic Developer
Validates trend quality metrics to refine automated trading logic.
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Bring your own AI
Change the model, client or framework. Keep Linear Regression Calculator connected.
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Before you connect
Questions about Linear Regression Calculator.
The practical details behind the request, access and result.
How can I use the Linear Regression Calculator MCP to predict prices?
You can use it to calculate the slope and intercept of a current trend, which allows your agent to project where the next price point is mathematically likely to land based on existing momentum.
Can the Linear Regression Calculator MCP help me find support and resistance?
Yes. By using the volatility channel feature, you can generate upper and lower boundaries that act as mathematical support and resistance levels based on standard deviation.
Is the Linear Regression Calculator MCP accurate for volatile markets?
The math is deterministic and precise, but the results depend on the data you provide. It's best used to quantify volatility rather than ignore it.
How does the Linear Regression Calculator MCP verify a trend?
It uses statistical fit metrics to determine how closely the actual price points follow the calculated regression line, helping you distinguish real trends from noise.
Which AI clients work with the Linear Regression Calculator MCP?
You can connect this MCP to any compatible client, including Claude, Cursor, Windsurf, and VS Code.
What mathematical method is used for the regression?
The server uses the Ordinary Least Squares (OLS) method to minimize the sum of the squares of the vertical deviations between the data points and the fitted line.
How can I determine if a trend is statistically significant?
You can use the analyze_trend_strength capability, which evaluates the R-squared value to categorize the fit quality as High, Moderate, or Low.
Can I predict future price values?
Yes, the calculate_regression_line capability provides a projection value, which is the mathematical extension of the regression line for the next period.
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