# EV Home Charging Scheduler AI Agent Connect

> EV Home Charging Scheduler MCP gives your AI client the math it needs to manage electric vehicle charging. It calculates precise charging windows based on your specific off-peak electricity periods, battery capacity, and charger power. Instead of guessing, you can use your agent to determine exactly when to start a charge to hit your target state of charge while minimizing costs.

## Overview
- **Category:** utilities
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_fu2oDG2WUxuVXD84uVtSGCwwoPNMjzWzmOtBKXzF/ai-agent-connect
- **Tags:** ev, charging, electricity, optimization, battery

## Description

Managing an electric vehicle means balancing battery needs with electricity costs. This MCP handles the math so you don't have to. You can give your AI client your specific off-peak hours and vehicle specs, and it will figure out the most efficient way to charge. It accounts for the energy lost during the conversion process and checks if your hardware can actually handle the load you're asking for. Whether you're trying to hit a specific percentage by morning or just want to make sure you're using the cheapest power available, this MCP provides the exact calculations for your charging schedule.

## Tools

### calculate_charging_window
This tool determines the specific start and end times for a charging session. It also checks if your target charge level was actually reached within those times.

### get_energy_requirement
Use this to find the exact amount of kWh needed to move your battery from one state of charge to another.

### summarize_charging_efficiency
This tool provides a summary of energy lost to heat and conversion during the charging process.

### validate_charger_capability
This tool checks if your charging hardware is physically capable of meeting the requested charge requirements.

## Prompt Examples

**Prompt:** 
```
Calculate a charging schedule for my EV. I have 40% charge, I want 80%, a 75kWh battery, a 7kW charger, 90% efficiency, and an off-peak window from 2024-05-01T01:00:00Z to 2024-05-01T06:00:00Z.
```

**Response:** 
```
The optimal charging window is from 2024-05-01T01:00:00Z to 2024-05-01T06:00:00Z. Total energy delivered to battery: 31.5 kWh. Target met.
```

**Prompt:** 
```
How much energy do I need to go from 20% to 90% on a 100kWh battery?
```

**Response:** 
```
You need 70 kWh to reach your target charge level.
```

**Prompt:** 
```
Can a 3kW charger handle a 100kWh battery for a standard overnight charge?
```

**Response:** 
```
The charger is capable of providing meaningful charge within a standard overnight window.
```

## Capabilities

### Off-peak scheduling
Your agent uses this to align charging times with the cheapest electricity windows.

### Energy loss calculation
The AI uses this to account for heat and conversion losses when estimating battery gains.

### Hardware verification
Your agent checks if your specific charger can handle the requested energy transfer.

### State of charge math
The AI calculates the exact kWh needed to move between specific battery percentages.

## Use Cases

### Nightly Charging Optimization
Your agent calculates exactly when to start charging to ensure you hit 80% charge by your morning commute using only off-peak power.

### Hardware Compatibility Checks
Before you plan a long charge, your agent verifies if your current charger can actually deliver the required energy.

### Energy Budgeting
You can determine the exact kWh needed for a specific trip based on your current battery percentage.

### Efficiency Auditing
Use the efficiency tool to see how much energy is being lost to heat during your charging cycles.

## Benefits

- Reduces electricity costs by targeting off-peak windows.
- Prevents hardware strain by validating charger capabilities.
- Provides accurate energy requirements by accounting for conversion losses.

## How It Works

Connect the MCP to your preferred client and start asking your agent to run energy calculations.

1. Connect your AI client to the Vinkius-hosted MCP.
2. Provide your vehicle battery capacity and current charge level to your agent.
3. Input your off-peak electricity window and charger power.
4. The agent uses the tools to calculate the optimal charging window and energy needs.

## Frequently Asked Questions

**How does this MCP help save money on EV charging?**
It calculates the best times to charge based on your specific off-peak electricity windows, ensuring you use the cheapest power available.

**Which AI clients can use this MCP?**
You can use this MCP with any compatible client like Claude, Cursor, Windsurf, or VS Code.

**Does it account for charging losses?**
Yes, the summarize_charging_efficiency tool accounts for energy lost to heat and conversion during the process.

**Can I check if my charger is powerful enough?**
Yes, the validate_charger_capability tool checks if your hardware can meet your specific charging requests.

**Do I need to host the MCP myself?**
No, Vinkius hosts and manages the MCP for you. You just connect your client and start using the tools.

**How does the tool handle electricity costs?**
The tool uses the provided off-peak windows to schedule charging when electricity is cheapest, ensuring you maximize savings.

**What happens if the charger is too slow to reach the target SoC?**
The `calculate_charging_window` tool will return the scheduled time and report the unmet energy in kWh that could not be delivered within the window.

**Does this account for charging losses?**
Yes, you can provide an efficiency decimal to account for energy lost to heat and conversion during the charging process.