# Stochastic Oscillator Calculator MCP for AI Agents AI Agent Connect

> Stochastic Oscillator Calculator MCP for technical analysis. It lets your AI agent compute %K and %D values, spot overbought or oversold market conditions, and identify price-momentum divergences to help you time entries and exits in financial markets.

## Overview
- **Category:** finance
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_iiPqGbIAvyqBo32ltaELFtuh5OyvRvgei3xvoh5e/ai-agent-connect
- **Tags:** stochastic, oscillator, momentum, trading, indicators, finance

## Description

Technical analysis often feels like a constant battle against manual math and squinting at charts. Instead of manually calculating momentum or hunting for divergences across multiple timeframes, you can hand those tasks over to your AI agent. This MCP gives your agent the ability to process price data and immediately output the specific oscillator metrics you need to make decisions. 

You can ask your agent to scan recent price action to see if the market is overextended or if momentum is starting to drift away from price movement. It handles the heavy lifting of calculating the core oscillator values and identifying the specific signal states that traders look for. By connecting this to your preferred AI client through the Vinkius catalog, you turn a standard chat interface into a sophisticated technical analysis workstation. You stop being a calculator and start being a strategist, focusing on the signals rather than the arithmetic.

## Tools

### get_oscillator_summary
Provides a high-level snapshot of the current market state. It gives you the big picture of momentum without the granular math.

### calculate_stochastic_metrics
Computes core %K and %D values. This tool identifies the specific signal states for your technical analysis.

### detect_stochastic_divergence
Finds discrepancies between price movement and momentum. It is essential for spotting potential trend reversals.

## Prompt Examples

**Prompt:** 
```
Calculate the stochastic metrics for these prices: High [10, 12, 11], Low [8, 9, 8], Close [9, 11, 10].
```

**Response:** 
```
Based on the data provided, here are the calculated values:

| Metric | Value |
| :--- | :--- |
| **%K** | [45.2, 78.5, 50.0] |
| **%D** | [40.1, 55.3, 58.2] |

**Current Status:** NEUTRAL
```

**Prompt:** 
```
Is the market currently overbought or oversold based on these %K values: [85, 88, 90] and %D values: [80, 82, 84]?
```

**Response:** 
```
The market is currently in the **OVERBOUGHT** zone. 

The most recent %K value is **90**, which indicates the asset is trading at the top of its recent range.
```

**Prompt:** 
```
Check for divergences using these prices: High [100, 110, 115], Low [50, 45, 40] and %K values: [50, 55, 52].
```

**Response:** 
```
A **BEARISH_DIVERGENCE** has been detected.

* **Price Action:** Reached a higher high of 115.
* **Momentum (%K):** Reached a lower high of 52.

This discrepancy suggests that despite the rising price, upward momentum is fading.
```

## Capabilities

### Calculate momentum metrics
Your agent computes precise %K and %D values from raw price data.

### Identify market extremes
The agent flags when assets are in overbought or oversold territory.

### Spot price-momentum divergences
Your agent detects when price trends and momentum indicators are moving in opposite directions.

### Summarize market trends
Get a high-level snapshot of current market momentum without digging through raw numbers.

### Detect signal crossovers
The agent identifies bullish and bearish crossovers between oscillator lines.

## Use Cases

### Spotting a trend reversal
A trader notices price making a new high but asks their agent to check if momentum is actually weakening via divergence detection.

### Filtering overextended entries
An analyst asks their agent to check if a recent price surge has pushed the oscillator into the overbought zone before entering a position.

### Automating signal checks
A user provides a list of recent highs and lows to their agent to quickly find where %K and %D crossovers have occurred.

### Rapid market scanning
An investor asks for a quick summary of current momentum to decide which assets are showing the strongest trends.

## Benefits

- Eliminate manual math by letting your agent handle all %K and %D calculations instantly.
- Catch trend reversals faster by using divergence detection to find price-momentum mismatches.
- Avoid overextended trades by having your agent flag overbought and oversold conditions.
- Speed up decision-making with quick market summaries that condense complex momentum data.
- Identify entry and exit signals through automated crossover detection.

## How It Works

The bottom line is you turn raw price data into actionable momentum signals through a simple conversation.

1. Provide your agent with recent price data including highs, lows, and closing prices.
2. The agent uses the connected tools to process the data and run the oscillator math.
3. You receive a clear breakdown of momentum states, divergences, or trend summaries.

## Frequently Asked Questions

**How can I use the Stochastic Oscillator Calculator MCP for my trading?**
You can use it to automate technical analysis. Your agent can calculate momentum values, identify overbought/oversold levels, and spot divergences in price action.

**Can this Stochastic Oscillator Calculator MCP detect trend reversals?**
Yes. By using the divergence detection capability, your agent can identify when price and momentum are moving in opposite directions, which is a common sign of a trend reversal.

**What data do I need to provide to the Stochastic Oscillator Calculator MCP?**
To get accurate results, you should provide your agent with a series of High, Low, and Closing prices for the period you want to analyze.

**Does the Stochastic Oscillator Calculator MCP work with any AI client?**
Yes, it works with any MCP-compatible client like Claude, Cursor, or Windsurf once you connect it through Vinkius.

**Can I get a quick summary of market momentum with this MCP?**
Yes. You can ask your agent for a high-level summary to get an immediate snapshot of the current market state without seeing all the raw math.

**What is the difference between Fast and Slow Stochastic?**
Fast Stochastic uses the raw %K calculation. Slow Stochastic applies smoothing to the %K values to reduce market noise, making it more reliable for trend identification.

**How do I detect a bullish crossover?**
A bullish crossover occurs when the %K line crosses above the %D line, indicating accelerating upward momentum.

**Can I use EMA instead of SMA for smoothing?**
Yes, the `calculate_stochastic_metrics` tool supports both SMA and EMA as moving average types for smoothing.