# ADX-Calculator MCP for AI Agents AI Agent Connect

> ADX-Calculator MCP provides deterministic trend strength and direction analysis using Wilder's smoothing. It allows your AI client to process price data to identify market trends, calculate directional indicators, and validate data integrity for technical analysis.

## Overview
- **Category:** finance
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_x9j9dF9vCT11dAX4cM6JSA9jntxQyMNmYbOlSTGW/ai-agent-connect
- **Tags:** adx, trading, indicators, wilder, finance

## Description

Calculating trend strength manually is a tedious process of crunching high, low, and close prices through complex smoothing formulas. This MCP changes that by giving your AI agent the ability to perform precise technical analysis on demand. Instead of you doing the math, you simply hand over your price arrays and let the agent determine if a market is trending or ranging. It uses Wilder's smoothing method to ensure the results match standard technical analysis expectations. You can check if your data is formatted correctly before running calculations, get a quick snapshot of the current trend state, or generate a full series of directional indicators. By connecting this to your workflow through Vinkius, you turn your AI client into a sophisticated quantitative analyst that can interpret market momentum in seconds.

## Tools

### calculate_adx_indicators
Generates the full set of ADX, +DI, and -DI metrics from price data. It provides the core math needed for deep trend analysis.

### get_latest_adx_summary
Returns the most recent trend state from a dataset. It's perfect for getting a quick pulse on current market momentum.

### validate_price_data
Checks if your high, low, and close price arrays are valid for calculation. It prevents errors by ensuring the data meets structural requirements.

## Prompt Examples

**Prompt:** 
```
Can you check the trend strength for these prices: High [150, 155, 152], Low [145, 148, 147], Close [148, 152, 150]?
```

**Response:** 
```
The trend analysis for that data shows:

| Metric | Value |
| :--- | :--- |
| **Trend Strength** | Weak Trend |
| **Directional Bias** | Uptrend |

The movement is currently showing low momentum.
```

**Prompt:** 
```
What's the current trend status for this data: High [10, 12, 11], Low [8, 9, 8], Close [9, 11, 10]?
```

**Response:** 
```
The most recent trend summary is:

* **ADX Value:** 22.5
* **Status:** Weak Trend
* **Bias:** Uptrend

The trend is present but lacks significant strength.
```

**Prompt:** 
```
Is this data enough to calculate a 14-period ADX?
```

**Response:** 
```
No, the data provided is insufficient. To perform a 14-period calculation, you need a larger set of price points to satisfy the smoothing requirements.
```

## Capabilities

### Measure trend strength
Get precise ADX values to determine if a market is actively trending or moving sideways.

### Identify directional bias
Determine whether the current momentum favors buyers or sellers using directional indicators.

### Validate price arrays
Ensure your high, low, and close price data is structurally sound before running math.

### Generate trend summaries
Get a quick, high-level overview of the most recent market state from a data set.

### Compute full indicator series
Produce a complete set of trend metrics for a provided range of price points.

## Use Cases

### Confirming momentum before a trade
A trader asks their agent to check if a recent price move is a real trend or just noise using calculate_adx_indicators.

### Automated trend monitoring
An analyst uses get_latest_adx_summary to quickly scan multiple assets for emerging directional bias.

### Cleaning messy data feeds
A developer uses validate_price_data to ensure a new data stream won't break their technical analysis logic.

### Backtesting trend strategies
A quant uses the full indicator series to evaluate how a trend-following strategy would have performed on historical data.

## Benefits

- Eliminate manual math errors by using deterministic Wilder's smoothing via calculate_adx_indicators.
- Save time on data prep by using validate_price_data to catch formatting issues early.
- Get instant market snapshots using get_latest_adx_summary instead of manual spreadsheet work.
- Improve entry precision by letting your agent identify strong trends through directional indicators.
- Reduce workflow friction by feeding raw price arrays directly into your analysis agent.

## How It Works

The bottom line is you provide the raw price data and get back professional-grade trend metrics.

1. Provide your price data arrays to your AI client.
2. The agent uses the MCP to validate the data and run the Wilder's smoothing calculations.
3. You receive a clear breakdown of trend strength and directional bias.

## Frequently Asked Questions

**How can I use ADX-Calculator to analyze market trends?**
You can provide your price data to your AI client, which then uses this MCP to calculate trend strength and direction, giving you an immediate read on market momentum.

**Does ADX-Calculator use standard smoothing methods?**
Yes, this MCP uses Wilder's smoothing method to ensure the trend calculations are consistent with standard technical analysis practices.

**Can I check if my price data is ready for analysis with ADX-Calculator?**
Yes, you can use the built-in validation tool to ensure your high, low, and close price arrays are correctly formatted before you attempt any calculations.

**Will ADX-Calculator work with my existing AI agent?**
Yes, as long as your agent is running in an MCP-compatible client like Claude, Cursor, or Windsurf, it can use these tools directly.

**Can I get a quick summary of a trend without full calculations?**
Yes, you can request a summary that provides the most recent trend state, which is much faster than generating a full historical series.

**What is the purpose of this tool?**
It calculates the Average Directional Index (ADX) to quantify trend strength and directional bias using high, low, and close price data.

**How is trend strength determined?**
A trend is considered strong when the ADX value exceeds 25.

**What data is required for calculation?**
You must provide arrays of high prices, low prices, and close prices. The arrays must have matching lengths and sufficient data points for the chosen period.