MCP For Claude Marketplace
Reconciliation Analysis

Reconciliation Analysis MCP Connector for Claude

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Analyze mine production discrepancies by comparing resource models, mine output, and mill feed.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides tools to perform mine reconciliation analysis. It connects AI agents to geological and production data to identify discrepancies in the mining value chain. Use get_reconciliation_factors to compare stages, calculate_model_accuracy to evaluate resource models, calculate_adjustment_factors for predictive corrections, and identify_discrepancy_sources to diagnose ore loss or dilution.

reconciliationmininggeologyproductionaccuracy

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

calculate_model_accuracy

Evaluates the reliability of the geological resource model against actual production data

get_reconciliation_factors

Compares different stages of the production chain to calculate specific reconciliation ratios

identify_discrepancy_sources

Diagnoses whether discrepancies are caused by geological estimation errors, mining dilution, or mill recovery issues

calculate_adjustment_factors

Generates correction coefficients to improve future model predictions based on historical reconciliation results

See how to talk to your AI agent using Reconciliation Analysis.

Calculate the reconciliation factor between the model and the mine.

The reconciliation factor between the model and the mine is 0.92, indicating a 8% discrepancy.

How accurate is the resource model for the current production data?

The model accuracy score is 0.95, which is considered High accuracy.

What is causing the discrepancy between the model, mine, and mill?

The primary source of discrepancy is Mining Dilution, with an estimated dilution percentage of 5.2%.

You can use the `get_reconciliation_factors` tool to compare the model stage with the mine stage.

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