# Sentiment vs Fundamental Divergence AI Agent Connect

> Identify arbitrage opportunities by detecting divergences between social hype and on-chain utility.

## Overview
- **Category:** analytics
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_XHZAXw3RRChwpfYcFEp8Tn41jJJDYYd91f3OQZPl/ai-agent-connect
- **Tags:** arbitrage, z-score, sentiment, fundamentals, prediction-markets

## Description

This MCP server provides deterministic trading signals by analyzing the statistical divergence between social media sentiment and on-chain fundamental metrics. By calculating Z-scores for both social volume and fundamental activity, it identifies 'Speculative Bubbles' (high hype, low utility) and 'Accumulation' phases (low hype, high utility). Use `calculate_divergence_signal` to generate BUY or SELL signals, `validate_stop_loss` to manage risk with a 15% threshold, and `get_historical_performance` to backtest the strategy against historical datasets.

## Tools

### get_historical_performance
Backtests the divergence strategy against historical data

### calculate_divergence_signal
Evaluates current market conditions to determine if a BUY or SELL signal is generated

### validate_stop_loss
Checks if a current position has reached the maximum allowable risk threshold

## Prompt Examples

**Prompt:** 
```
Analyze the current divergence for a crypto asset with a market price of 0.5, social volume of 100, fundamental metric of 50, and historical data provided.
```

**Response:** 
```
The current signal is SELL because the social Z-score is 2.5 (high hype) while the fundamental Z-score is -0.5 (declining utility).
```

**Prompt:** 
```
Check if my BUY position at 0.8 is still valid if the current price is 0.68.
```

**Response:** 
```
The stop-loss has been triggered. The price movement is 15% below your entry price.
```

**Prompt:** 
```
What is the historical win rate for this strategy using the provided dataset?
```

**Response:** 
```
The strategy has a historical win rate of 62% across 145 total signals generated.
```

## Frequently Asked Questions

**How are the trading signals generated?**
Signals are generated using `calculate_divergence_signal`, which compares the Z-score of social volume against the Z-score of fundamental metrics to find extreme divergences.

**What is the risk management strategy?**
The strategy uses a strict 15% stop-loss. You can use `validate_stop_loss` to check if a position should be exited based on adverse price movement.

**Can I backtest this strategy?**
Yes, the `get_historical_performance` tool allows you to run the divergence strategy against historical snapshots to calculate the win rate.