Kaufman Adaptive Moving Average (KAMA) Calculator Connector for AI agents.
3 live capabilities
Calculate adaptive moving averages that adjust to market volatility
Waiting for input…
Why people use Kaufman Adaptive Moving Average (KAMA) Calculator
Stop getting chopped by market noise with Kaufman Adaptive Moving Average
With this MCP, your agent does the heavy lifting. You simply hand over the price data, and it applies the Kaufman logic to filter out the noise. You get clear, mathematically sound trend signals that adapt to the market's speed automatically.
What Vinkius changes
You get mathematically adaptive trend indicators that react to volatility in real-time.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Filtering choppy markets
A trader asks their agent to check if a stock is trending or just ranging.
- Real-world use case 02
Automated trend following
An analyst provides a week of closing prices.
- Real-world use case 03
Real-time monitoring
A user wants to know the current trend direction.
Complete set · 3capabilities
The complete Kaufman Adaptive Moving Average (KAMA) Calculator capability set.
These are the exact actions your AI can choose when you ask it to work with Kaufman Adaptive Moving Average (KAMA) Calculator.
01—03
3 capabilities in this set.
Part of 3 available through Kaufman Adaptive Moving Average (KAMA) Calculator.
- 01 Capability
Analyze kama volatility regime
Determines if the market is currently in a trending or ranging regime. It uses recent movement efficiency to classify the volatility state.
- 02 Capability
Calculate kama series
Computes a full sequence of KAMA values and trend metrics. It processes a provided set of prices into a complete dataset.
- 03 Capability
Get latest kama status
Extracts the most recent trend and volatility data. It pulls current metrics from a previously calculated series.
Set up in minutes
One URL. Then ask Kaufman Adaptive Moving Average (KAMA) Calculator to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Kaufman Adaptive Moving Average (KAMA) 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_QeHHBMLTwx6vQSFHoSo9kqveZm5WAXFYa3h5Xtzj/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 Kaufman Adaptive Moving Average (KAMA) Calculator, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Kaufman Adaptive Moving Average (KAMA) Calculator for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_QeHHBMLTwx6vQSFHoSo9kqveZm5WAXFYa3h5Xtzj/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 Kaufman Adaptive Moving Average (KAMA) Calculator URL.
- Step 03
Save and start
Save the connection and enable Kaufman Adaptive Moving Average (KAMA) Calculator in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"kaufman-adaptive-moving-average-kama-calculator": {
"url": "https://edge.vinkius.com/vk_preview_QeHHBMLTwx6vQSFHoSo9kqveZm5WAXFYa3h5Xtzj/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 Kaufman Adaptive Moving Average (KAMA) Calculator
Open Agent mode in chat and ask: "Using Kaufman Adaptive Moving Average (KAMA) Calculator, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"kaufman-adaptive-moving-average-kama-calculator": {
"url": "https://edge.vinkius.com/vk_preview_QeHHBMLTwx6vQSFHoSo9kqveZm5WAXFYa3h5Xtzj/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 Kaufman Adaptive Moving Average (KAMA) Calculator
Ask Copilot: "Using Kaufman Adaptive Moving Average (KAMA) Calculator, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"kaufman-adaptive-moving-average-kama-calculator": {
"url": "https://edge.vinkius.com/vk_preview_QeHHBMLTwx6vQSFHoSo9kqveZm5WAXFYa3h5Xtzj/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 Kaufman Adaptive Moving Average (KAMA) Calculator
Open Cascade and ask: "Using Kaufman Adaptive Moving Average (KAMA) Calculator, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"kaufman-adaptive-moving-average-kama-calculator": {
"url": "https://edge.vinkius.com/vk_preview_QeHHBMLTwx6vQSFHoSo9kqveZm5WAXFYa3h5Xtzj/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 Kaufman Adaptive Moving Average (KAMA) Calculator
Ask Cline: "Using Kaufman Adaptive Moving Average (KAMA) Calculator, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add kaufman-adaptive-moving-average-kama-calculator --transport http "https://edge.vinkius.com/vk_preview_QeHHBMLTwx6vQSFHoSo9kqveZm5WAXFYa3h5Xtzj/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 Kaufman Adaptive Moving Average (KAMA) Calculator
Ask Claude: "Using Kaufman Adaptive Moving Average (KAMA) Calculator, show me...". 3 tools are ready
Where the request belongs
Work Kaufman Adaptive Moving Average can move forward.
This is built for quantitative traders and technical analysts who need indicators that don't lag during breakouts or get chopped up in sideways markets.
Quantitative Trader
Uses KAMA to build trend-following strategies that adapt to changing volatility.
Technical Analyst
Identifies market regimes to decide whether to use trend-following or mean-reversion setups.
Algorithmic Developer
Integrates deterministic KAMA calculations into automated trading logic via AI agents.
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Before you connect
Questions about Kaufman Adaptive Moving Average.
The practical details behind the request, access and result.
How does the Kaufman Adaptive Moving Average MCP help with trading?
It provides an adaptive trend indicator that automatically speeds up during strong trends and slows down during sideways markets, helping you avoid false signals.
Can I use this Kaufman Adaptive Moving Average MCP in Claude?
Yes, once you connect this MCP through Vinkius, you can use it directly within Claude or any other MCP-compatible client.
How does this MCP distinguish between trending and ranging markets?
It uses an Efficiency Ratio to measure how much price movement is actual progress versus noise, allowing it to classify the market regime.
Is this Kaufman Adaptive Moving Average MCP useful for backtesting?
Absolutely. You can provide historical price series to your agent to generate full datasets of adaptive trend values for testing strategies.
What makes KAMA different from a standard moving average?
Unlike standard averages that have a fixed lag, KAMA adjusts its smoothing speed based on market volatility to be more responsive when it matters most.
One connection away
Give your agent a direct line to Kaufman Adaptive Moving Average.
Connect Kaufman Adaptive Moving Average once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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