# assignment-weighted-grade is a grading engine. AI Agent Connect

> assignment-weighted-grade handles the math behind weighted grading systems. Your AI client uses this MCP to determine how specific assignments impact final scores, verify that weight distributions are mathematically sound, and pull together performance summaries across multiple grading periods without manual calculation errors.

## Overview
- **Category:** productivity
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_O0ia2nJyypLtkLvM23w0dE0WDuqdHXZp90ry8UhD/ai-agent-connect
- **Tags:** grading, weighted-average, academic, calculation, performance

## Description

You can stop manually calculating weighted averages in spreadsheets. This MCP gives your AI client the math logic needed to handle complex academic or professional grading structures. Instead of guessing how a single quiz affects a final grade, you can ask your agent to run the numbers using specific weights. It handles the heavy lifting of verifying that your weight distributions actually add up to the correct total, preventing errors before they hit your gradebook. Whether you are looking at a single assignment's impact or need a high-level view of how performance has shifted over several grading periods, this tool provides the exact figures you need. It is built for accuracy in environments where every percentage point matters.

## Tools

### calculate_period_grade
This tool computes the total weighted grade for a full set of assignments within a single grading period.

### get_assignment_contribution
Use this to find out exactly how many points a specific assignment adds to the final total grade.

### get_performance_summary
This tool generates a high-level overview of performance across various grading periods.

### validate_weight_distribution
This tool checks if a set of weights is mathematically valid for a specific grading period.

## Prompt Examples

**Prompt:** 
```
How much does an assignment with a score of 80/100 and a weight of 0.2 contribute to the final grade?
```

**Response:** 
```
The assignment contributes 16 points to the final grade.
```

**Prompt:** 
```
Calculate the total grade for assignments: {rawScore: 90, maxScore: 100, weight: 0.5} and {rawScore: 70, maxScore: 100, weight: 0.5}.
```

**Response:** 
```
The final grade is 80.
```

**Prompt:** 
```
Are weights [0.3, 0.3, 0.3] valid for an expected total of 1.0?
```

**Response:** 
```
No, the weights are not valid as they sum to 0.9, resulting in a variance of 0.1.
```

## Capabilities

### Weighted Grade Calculation
Your agent calculates total grades for any set of assignments based on assigned weights.

### Weight Validation
The AI checks if your weight distributions are mathematically correct.

### Individual Impact Analysis
Your agent determines the specific point contribution of a single task.

### Performance Tracking
The AI pulls together summaries of performance across different timeframes.

## Use Cases

### Grading Period Totals
An instructor uses the agent to sum up all weighted scores at the end of a semester.

### Weight Verification
A curriculum designer checks if a new syllabus weight distribution is mathematically valid.

### Student Progress Reports
An administrator asks for a performance summary to see how a cohort is trending over time.

### Single Task Impact
A student asks their agent how much a specific upcoming exam will change their final grade.

## Benefits

- Eliminates manual calculation errors in weighted grading.
- Provides instant verification of weight distributions.
- Automates the process of determining individual assignment impact.
- Generates multi-period performance overviews quickly.

## How It Works

Connecting this MCP to your AI client gives your agent immediate access to grading math tools.

1. Connect your preferred MCP-compatible client to Vinkius.
2. The assignment-weighted-grade MCP becomes available in your agent's toolset.
3. Provide your assignment scores and weights to your agent.
4. The agent executes the necessary calculation tools to return precise results.

## Frequently Asked Questions

**What can this MCP calculate?**
It calculates weighted period grades, individual assignment contributions, and performance summaries.

**Can it check if my weights are correct?**
Yes, it uses the validate_weight_distribution tool to ensure your weights are mathematically valid.

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

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

**How does it handle multiple grading periods?**
The get_performance_summary tool allows your agent to look at performance across different periods.

**How do I calculate a single assignment's impact?**
You can use the `get_assignment_contribution` tool by providing the raw score, the maximum possible score, and the weight of the assignment.

**Can I verify if my weights add up to 100%?**
Yes, the `validate_weight_distribution` tool checks if a set of weights matches your expected total.

**How do I get a summary of multiple grading periods?**
Use the `get_performance_summary` tool to receive an overview including average, highest, and lowest grades.