# Price Forecast Model AI Agent Connect

> Generate energy price trajectories, confidence intervals, and market scenario probabilities.

## Overview
- **Category:** finance
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_nxd0M5fGoYDOgkJRXRKQZzSaQ4TLHzPYZGQM6sHM/ai-agent-connect
- **Tags:** oil, gas, forecasting, commodities, economics

## Description

This MCP server provides advanced analytical tools for energy market forecasting. It allows AI agents to calculate expected price trajectories using `get_price_trajectory`, assess market uncertainty with `get_price_confidence_intervals`, and determine the likelihood of Bullish or Bearish outcomes via `get_scenario_probabilities`. Additionally, users can identify market mispricing by using `analyze_curve_vs_history` to compare forward curves against historical data.

## Tools

### get_scenario_probabilities
Determine the likelihood of different market directions (Bullish, Bearish, Neutral) based on supply/demand and macro inputs

### analyze_curve_vs_history
Compare current market forward curves against historical price patterns to identify market mispricing or extreme sentiment

### get_price_confidence_intervals
Understand the range of potential price outcomes and the level of uncertainty in the forecast

### get_price_trajectory
Retrieve the central predicted price path for a specific commodity over a given timeframe

## Prompt Examples

**Prompt:** 
```
What is the expected price path for crude oil over the next 12 months?
```

**Response:** 
```
The expected price for crude oil is projected to follow a steady upward trend, reaching approximately $85 per barrel by month 12.
```

**Prompt:** 
```
What is the 95% confidence interval for natural gas prices for a 6-month horizon?
```

**Response:** 
```
For a 6-month horizon, the 95% confidence interval for natural gas ranges from $2.50 to $4.10 per MMBtu.
```

**Prompt:** 
```
How likely is a bearish scenario if there is a significant supply increase?
```

**Response:** 
```
A significant supply increase shifts the market probability toward a Bearish case, with a calculated likelihood of 65%.
```

## Frequently Asked Questions

**What commodities can I forecast?**
The model supports primary energy benchmarks including crude oil, natural gas, and regional commodities like European natural gas or diesel.

**How are the price trajectories calculated?**
Trajectories are calculated by integrating historical prices, forward curves, and supply/demand fundamentals, while accounting for seasonality and mean reversion.

**Can I model specific supply shocks?**
Yes, you can use `get_scenario_probabilities` with the `supplyShockMagnitude` parameter to see how unexpected supply changes affect market probabilities.