# Futures Carry Trade Strategy MCP for AI Agents AI Agent Connect

> Futures Carry Trade Strategy MCP identifies arbitrage opportunities by comparing implied market carry against theoretical cost-of-carry models. It calculates the spread between market prices and the risk-free rate, storage costs, and convenience yields to pinpoint profitable trades in contango or backwardation regimes.

## Overview
- **Category:** finance
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_Jalvs3ofGZwWeTvre8yohLc3jfUrcmB234jaPf9Z/ai-agent-connect
- **Tags:** futures, carry-trade, arbitrage, quantitative, commodities

## Description

This MCP gives your AI agent a deterministic engine for executing futures carry trade strategies. Instead of guessing if a curve is mispriced, you can immediately see the gap between implied market carry and the theoretical cost-of-carry. It handles the heavy lifting of factoring in risk-free rates, storage costs, and convenience yields to find arbitrage. You can check the current state of the futures curve to see if the market is in contango or backwardation, then pull specific signals to decide whether to buy or sell. It also lets you look backward to see how these strategies actually performed, calculating historical P&L and roll-down returns so you aren't flying blind. By connecting this to your preferred AI client through the Vinkius catalog, you turn a standard chat interface into a quantitative trading workstation that understands the nuances of commodity and financial futures curves.

## Tools

### analyze_market_regime
Classifies whether the current futures curve is in contango or backwardation. This helps you understand the fundamental market structure.

### calculate_carry_performance
Computes historical P&L and roll-down returns for your strategies. It provides a clear view of how carry trades would have performed.

### get_daily_signals
Produces buy or sell signals by comparing market carry to theoretical models. It identifies the exact moments when arbitrage exists.

## Prompt Examples

**Prompt:** 
```
Should I buy or sell based on these prices? Front: 100, Second: 105, Risk-free: 0.05, Storage: 0.01, Yield: 0.02, Days: 30.
```

**Response:** 
```
The signal is **BUY**. 

| Metric | Value |
| :--- | :--- |
| Implied Carry | 16.1% |
| Theoretical Carry | 4.0% |

There is a significant arbitrage opportunity here as the implied carry exceeds the theoretical cost-of-carry.
```

**Prompt:** 
```
Is the market in contango or backwardation if the front month is 50 and the next is 48?
```

**Response:** 
```
The market is currently in **Backwardation**. This indicates that the immediate supply is more highly valued than future delivery.
```

**Prompt:** 
```
How did my last buy signal perform with these prices: [100, 105]?
```

**Response:** 
```
Based on the signal history provided:

* **Cumulative Carry P&L:** 5.0
* **Roll-down Return:** 2.5

The strategy captured significant value from the price movement.
```

## Capabilities

### Identify arbitrage gaps
Find discrepancies between implied market carry and theoretical cost-of-carry models.

### Classify market regimes
Determine if the current futures curve is in a state of contango or backwardation.

### Generate trading signals
Get clear buy or sell directions based on current market pricing and theoretical models.

### Audit historical performance
Analyze past P&L and roll-down returns to validate strategy effectiveness.

## Use Cases

### Spotting Contango mispricings
A trader notices widening spreads in oil futures and uses get_daily_signals to confirm if the implied carry justifies a long position.

### Validating a new strategy
An analyst uses calculate_carry_performance to check if a specific roll-down strategy would have survived recent market volatility.

### Monitoring supply shortages
A commodity desk uses analyze_market_regime to detect a shift into backwardation, signaling tight physical supply.

### Automating signal checks
A quant uses their agent to run daily checks on multiple commodity curves to find the highest carry opportunities.

## Benefits

- Eliminate manual math by using get_daily_signals to find arbitrage gaps instantly.
- Understand market structure immediately by using analyze_market_regime to detect contango or backwardation.
- Validate your assumptions using calculate_carry_performance to see real historical P&L.
- Stop guessing on roll-down returns by getting precise mathematical calculations from your agent.
- Speed up decision making by turning raw price data into direct buy or sell signals.

## How It Works

The bottom line is you turn raw futures pricing data into precise arbitrage signals.

1. Connect your AI client to the MCP via Vinkius
2. Provide market data like front-month prices, storage costs, and risk-free rates
3. Receive actionable signals or regime classifications based on the mathematical model

## Frequently Asked Questions

**How can I use the Futures Carry Trade Strategy MCP to find arbitrage?**
You provide your agent with current market prices, storage costs, and interest rates. The MCP then calculates the difference between the market's implied carry and the theoretical cost-of-carry to identify mispriced opportunities.

**Can this Futures Carry Trade Strategy MCP detect market regimes?**
Yes. It can instantly classify whether a futures curve is in a state of contango or backwardation, which is essential for understanding market structure.

**Will the Futures Carry Trade Strategy MCP work with my existing AI client?**
Yes, as long as your client is MCP-compatible, such as Claude, Cursor, or Windsurf, you can connect it through Vinkius and start using it immediately.

**How does the Futures Carry Trade Strategy MCP handle historical data?**
It includes tools to analyze historical profitability, allowing you to check the P&L and roll-down returns of specific signals to see how they would have performed in the past.

**Does the Futures Carry Trade Strategy MCP provide specific buy or sell directions?**
Yes. It generates specific trading signals by comparing the market's implied carry against the theoretical model, telling you whether to buy or sell.