# Scooter Charge & Range Planner AI Agent Connect

> Scooter Charge & Range Planner MCP gives your AI client the ability to handle electric scooter energy constraints. It calculates if trips are possible based on current battery levels and safety reserves, plans where to stop for a charge, and validates that your range parameters make sense for real-world operations.

## Overview
- **Category:** logistics
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_oCunv1vpBbQGpkcdHLkqfntAfglVqnzoHz2AC1ge/ai-agent-connect
- **Tags:** scooter, battery, range, ev, logistics

## Description

You can stop guessing if a scooter has enough charge to finish a route. This MCP gives your agent the math it needs to handle electric scooter energy constraints. Instead of manually checking battery percentages against distance, you let your AI client run the numbers. It looks at your current battery state, accounts for the safety reserves you require, and tells you if a single trip or a whole sequence of stops is actually doable. If a route looks impossible, the MCP can identify exactly where a charging stop should happen to make the plan work. It also checks your operational logic to ensure your range constraints are physically possible before you send a driver out. It's a direct way to turn your AI agent into a logistics coordinator that understands battery physics.

## Tools

### get_scooter_status_summary
Use this to get a quick overview of the scooter's current energy state and total capacity.

### calculate_trip_feasibility
This tool checks if a single trip or a series of trips can be completed using the current battery level.

### plan_optimized_charging
This tool finds the best spot for a charging stop to turn an impossible trip into a feasible one.

### validate_range_parameters
This tool confirms that your range-related constraints are logically sound and physically possible.

## Prompt Examples

**Prompt:** 
```
Can a scooter with 50% battery and a 60km full range complete two 12km trips with a 10% safety reserve?
```

**Response:** 
```
Yes, the trips are feasible. After accounting for the 10% safety reserve, the scooter has enough remaining charge to cover the 24km total distance.
```

**Prompt:** 
```
Give me a summary of a scooter with 80% battery, 50km full range, and a 15% safety reserve.
```

**Response:** 
```
The scooter has a usable range of 35km, a reserve range of 7.5km, and a total current range of 40km.
```

**Prompt:** 
```
Is it possible to complete a 40km trip if the scooter has 30% battery and a 100km full range, with a 10% reserve?
```

**Response:** 
```
No, the trip is not feasible. The available range after the 10% reserve is only 20km, which is insufficient for a 40km trip.
```

## Capabilities

### Trip Feasibility Checks
Your agent determines if a route is possible before a driver starts moving.

### Energy Status Overviews
The AI gets a clear picture of usable range versus total capacity.

### Charging Stop Optimization
Your agent identifies where to add a charge to fix an impossible route.

### Constraint Validation
The AI verifies that your range and safety settings are realistic.

## Use Cases

### Multi-stop Route Planning
Check if a scooter can hit five different delivery points in one go without needing a charge.

### Safety Reserve Management
Ensure every trip maintains a specific percentage of battery as a buffer.

### Charging Station Placement
Determine the best time to stop for a charge to keep a long route viable.

### Operational Logic Audits
Verify that your fleet's range settings aren't mathematically impossible.

## Benefits

- Prevents scooters from running out of power mid-trip.
- Automates the math for safety reserves and usable range.
- Identifies necessary charging stops within a trip sequence.
- Ensures operational parameters stay within physical limits.

## How It Works

Get your AI client connected to the Vinkius hosted MCP to start managing scooter energy.

1. Connect your AI client to Vinkius with one click.
2. Provide the scooter's current battery and range data to your agent.
3. Ask the agent to calculate a trip or check a status.
4. The agent uses the MCP tools to run the math and return a result.

## Frequently Asked Questions

**How does the MCP handle safety reserves?**
The MCP subtracts the required safety reserve from the total available range to calculate the actual usable distance for a trip.

**Can I plan multiple trips at once?**
Yes, the calculate_trip_feasibility tool can evaluate a single trip or a whole sequence of trips.

**What happens if a trip is impossible?**
The plan_optimized_charging tool can identify if adding a charging stop at a specific point makes the sequence feasible.

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

**Do I need to host the MCP myself?**
No, Vinkius hosts and manages the MCP for you, so it is ready to use immediately after connection.

**How can I check if my scooter can complete a specific route?**
You can use the `calculate_trip_feasibility` tool by providing the current battery percentage, the total range of the scooter, and the distances of your planned trips.

**What is the purpose of the safety reserve?**
The safety reserve is a mandatory battery percentage that must remain untouched to ensure the rider can safely reach a charging station or destination.

**Can I simulate the effect of a charging stop?**
Yes, the `plan_optimized_charging` tool allows you to simulate adding a charge at a specific point in your trip sequence to see if it makes the plan feasible.