# Percentage Price Oscillator (PPO) Engine MCP for AI Agents AI Agent Connect

> Percentage Price Oscillator (PPO) Engine is a deterministic momentum engine for financial analysis. It calculates normalized momentum indicators, allowing you to compare price strength across different assets regardless of their nominal price. Use it to find divergences, detect signal crossovers, and compare momentum against standard MACD metrics.

## Overview
- **Category:** finance
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_xtds9hLo1RAwvVHXOE2svRSwTRIKvg1EQtSw0q6A/ai-agent-connect
- **Tags:** momentum, ema, trading, indicators, ppo, macd

## Description

This MCP gives your AI agent a precise way to measure price momentum using the Percentage Price Oscillator. While standard indicators often struggle when comparing a high-priced stock to a low-priced one, this engine uses normalized percentages to keep everything on a level playing field. You can ask your agent to run full momentum suites, find where price action and momentum are drifting apart, or spot specific triggers like zero-line crosses. It's built for traders and analysts who need consistent, repeatable math rather than vague guesses. By connecting this to your preferred AI client through the Vinkius catalog, you turn a standard chat interface into a technical analysis workstation that can spot trends and momentum shifts in seconds.

## Tools

### calculate_ppo_metrics
Calculates the full suite of PPO indicators. It generates the oscillator, signal line, and histogram for any price series.

### compare_with_macd
Provides a comparative analysis between PPO and standard MACD. This helps you see the difference between percentage-based and absolute momentum.

### detect_ppo_divergence
Finds discrepancies between price movements and PPO momentum. It identifies when price and momentum are moving in opposite directions.

### detect_ppo_events
Identifies specific momentum triggers. It flags zero-line crosses and signal crossovers in your data.

## Prompt Examples

**Prompt:** 
```
Can you run the PPO metrics for these closing prices: [150.2, 152.5, 151.0, 153.4, 155.0, 154.2, 156.8]?
```

**Response:** 
```
Here are the PPO metrics for that price series:

| Metric | Value |
| :--- | :--- |
| **PPO Oscillator** | 0.45 |
| **Signal Line** | 0.32 |
| **Histogram** | 0.13 |

The momentum is currently positive, with the oscillator sitting above the signal line.
```

**Prompt:** 
```
Are there any bullish divergences in this price series: [100, 105, 102, 108, 104, 110]?
```

**Response:** 
```
I checked the price series for divergences.

**Result:** No bullish divergences were detected in the provided price series. The price action and momentum appear to be moving in relative sync.
```

**Prompt:** 
```
Compare the PPO and MACD for these prices: [50, 51, 52, 51, 50, 49].
```

**Response:** 
```
Comparing the two momentum indicators for your data:

* **PPO:** Shows a momentum decline of **-0.15%**.
* **MACD:** Shows an absolute difference of **-0.45**.

The PPO provides a normalized view of the momentum decay, while the MACD shows the absolute distance.
```

## Capabilities

### Generate momentum metrics
Produces the full suite of oscillator, signal line, and histogram values.

### Spot price-momentum discrepancies
Identifies divergences where price movement and momentum are no longer in sync.

### Identify momentum triggers
Flags specific events like signal crossovers or zero-line crossings.

### Compare momentum types
Provides a direct comparison between PPO and standard MACD values.

## Use Cases

### Comparing high-priced stocks to penny stocks
An analyst needs to see if momentum is similar across two very different assets. They ask their agent to use calculate_ppo_metrics to get normalized values for both.

### Spotting exhausted trends
A trader suspects a rally is losing steam. They ask their agent to use detect_ppo_divergence to see if the price is still climbing while momentum is dropping.

### Automating signal detection
A researcher wants to find specific entry points. They ask their agent to use detect_ppo_events to find every time the signal line crossed the zero line in a dataset.

### Validating MACD strategies
A user wants to know if their MACD signals are too aggressive. They ask their agent to use compare_with_macd to see how the normalized PPO differs from the absolute MACD.

## Benefits

- Compare momentum across different assets easily using calculate_ppo_metrics to get normalized percentage values.
- Find hidden trend reversals by using detect_ppo_divergence to spot price and momentum mismatches.
- Automate entry and exit signals by using detect_ppo_events to catch zero-line and signal crossovers.
- Differentiate between absolute and percentage momentum by using compare_with_macd for deeper context.
- Get consistent, deterministic math every time you ask your agent to analyze a price series.

## How It Works

The bottom line is you turn raw price data into actionable momentum signals.

1. Provide a series of closing prices to your AI client.
2. The engine processes the price data through the PPO mathematical model.
3. Your agent returns specific momentum indicators, divergences, or crossover events.

## Frequently Asked Questions

**How does the Percentage Price Oscillator (PPO) MCP help with comparing different stocks?**
It uses normalized percentage values instead of absolute price differences. This allows you to compare the momentum of a high-priced stock and a low-priced stock on the same scale.

**Can I use the Percentage Price Oscillator (PPO) Engine to find trend reversals?**
Yes. You can ask your agent to use the divergence and event detection tools to find where price and momentum are splitting or where signal crossovers are occurring.

**What is the difference between PPO and MACD in this MCP?**
The engine includes a specific tool to compare the two. While MACD uses absolute differences, PPO uses percentages, making it easier to compare momentum across different assets.

**Can my AI agent detect signal crossovers automatically?**
Yes. By using the event detection tool, your agent can identify specific triggers like zero-line crosses and signal line crossovers in your price data.

**Do I need to provide my own price data to the Percentage Price Oscillator (PPO) Engine?**
Yes. You provide the price series to your AI client, and the engine performs all the mathematical calculations to return the indicators you need.

**How is PPO different from MACD?**
MACD measures the absolute difference between EMAs, while PPO measures the percentage difference. This normalization makes PPO better for comparing momentum across different assets with different price scales.

**What are the default periods for the calculation?**
The default settings are a fast period of 12, a slow period of 26, and a signal period of 9.

**Can I detect trend reversals using this server?**
Yes, you can use `detect_ppo_events` to find zero-line crosses and signal crossovers, which are common indicators of momentum shifts and potential trend reversals.