assignment-weighted-grade

assignment-weighted-grade MCP Connector for Claude

A+

Calculate precise weighted grades and performance summaries.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides a specialized calculation engine for academic and professional grading. It allows AI agents to determine how much a single task contributes to a final grade using get_assignment_contribution, calculate total grades for a grading period with calculate_period_grade, verify weight distributions with validate_weight_distribution, and generate high-level performance overviews using get_performance_summary.

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4 tools expose this connector's capabilities to your AI agent.

calculate_period_grade

Calculates the total weighted grade for a complete set of assignments within one grading period

get_assignment_contribution

Calculates how many points a single assignment contributes to the final total grade

get_performance_summary

Provides a high-level overview of performance across multiple different grading periods

validate_weight_distribution

Checks if a set of weights is mathematically valid for a single grading period

See how to talk to your AI agent using assignment-weighted-grade.

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

The assignment contributes 16 points to the final grade.

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

The final grade is 80.

Are weights [0.3, 0.3, 0.3] valid for an expected total of 1.0?

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

You can use the `get_assignment_contribution` tool by providing the raw score, the maximum possible score, and the weight of the assignment.

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