# Board Game Score Calculator MCP. AI Agent Connect

> Board Game Score Calculator MCP handles the heavy lifting of game math. It processes player actions and resource values to produce accurate scorecards, resolve complex tie-breaks, and provide a full audit trail for every point earned. You can connect it to your AI client to automate the final stages of any tabletop game session.

## Overview
- **Category:** utilities
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_V37KIRjTnodapTwgT1wA93qZOidC0mNuduIbMlpB/ai-agent-connect
- **Tags:** scoring, board-games, rankings, audit, game-engine

## Description

You can stop manually tallying points and arguing over tie-break rules. This MCP acts as a high-precision engine that converts granular player actions and resource counts into finalized rankings. If you feed your agent the raw data from a session, it can generate detailed scorecards that break down exactly how every player reached their total. 

When games get complicated, the engine handles hierarchical tie-breaking to ensure winners are determined without error. It also provides a layer of mathematical integrity. You can ask your agent to verify a specific player's score or check if the entire scoring logic holds up against the provided data. It's built to ensure that the final standings are consistent and easy to audit, making it a reliable tool for complex tabletop simulations or heavy strategy games.

## Tools

### calculate_player_scorecards
This tool generates a detailed breakdown of points for every player in the session.

### generate_final_rankings
This tool produces an ordered list of player IDs by applying specific score totals and tie-break rules.

### get_score_audit_trail
This tool provides a mathematical verification of a specific player's total score.

### validate_scoring_logic
This tool checks the provided scoring data to ensure it is logically consistent.

## Prompt Examples

**Prompt:** 
```
Calculate the scorecards for these players: Player1 has 10 points from actions and 5 resource value. Player2 has 12 points from actions and 2 resource value.
```

**Response:** 
```
Player1: 15 total points. Player2: 14 total points.
```

**Prompt:** 
```
Who won the game based on these scorecards: Player1 (20 pts), Player2 (20 pts), Player3 (15 pts) with tie-break on resourceValue?
```

**Response:** 
```
The winners are Player1 and Player2, followed by Player3.
```

**Prompt:** 
```
Verify the score for Player1 using these scorecards: Player1 (Total 25, Actions 20, Resources 5, Bonuses 0, Penalties 0).
```

**Response:** 
```
The audit for Player1 is verified: 20 (actions) + 5 (resources) + 0 (bonuses) - 0 (penalties) = 25.
```

## Capabilities

### Scorecard Generation
Your agent uses this to create itemized point breakdowns for every participant.

### Tie-Break Resolution
The agent applies hierarchical rules to determine winners when scores are identical.

### Mathematical Auditing
Your agent can verify that a player's total matches the sum of their individual actions.

### Logic Validation
The agent checks the dataset to ensure no scoring rules have been violated.

### Ranked Standings
The agent produces a clean, ordered list of players based on final results.

## Use Cases

### Complex Strategy Games
Use the agent to process multi-variable scores from heavy Euro-style board games.

### Tournament Management
Generate final player rankings and winner lists from a pool of session data.

### Game Rule Testing
Validate that your custom scoring logic produces consistent and logical results.

### Score Verification
Run an audit on a player's score to confirm their total is mathematically correct.

## Benefits

- Eliminates manual calculation errors in complex scoring systems.
- Provides a verifiable audit trail for every point awarded.
- Resolves ties automatically using predefined hierarchical rules.
- Ensures data consistency across all player records.

## How It Works

Connect the MCP to your client and start feeding it game data.

1. Connect your MCP-compatible client to Vinkius.
2. Provide your agent with raw player actions and resource values.
3. Instruct the agent to calculate scorecards or rankings.
4. Review the generated results or audit trails for accuracy.

## Frequently Asked Questions

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

**How does the tie-breaking work?**
The engine uses hierarchical tie-breaking rules to resolve winners when players have identical scores.

**Can I verify if a score is correct?**
Yes, you can use the audit tool to check the mathematical integrity of any player's score.

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

**Can it handle complex scoring rules?**
Yes, the tool is designed to handle granular player actions and multiple resource values to create detailed scorecards.

**How does the engine handle tied players?**
Ties are resolved using the `generate_final_rankings` tool, which accepts a prioritized list of tie-break criteria to ensure stable and predictable rankings.

**Can I verify the math behind a specific player's score?**
Yes, you can use `get_score_audit_trail` to receive a detailed breakdown of all components used to calculate a player's total score.

**What data is required for scoring?**
The engine requires player actions, resource values, objectives met, and any applicable bonuses or penalties.