MCP For Claude Marketplace
Multi-Modal AI Economics Engine

Multi-Modal AI Economics Engine MCP Connector for Claude

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Calculate multi-modal AI costs, margins, and optimal pricing strategies.

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

This MCP server provides a specialized economic engine for multi-modal AI workloads. It allows agents to calculate the total cost of requests by accounting for text tokens, image counts, audio, and video durations, while factoring in multi-modal fusion overhead and model switching costs. Use calculate_request_cost to determine total expenses, analyze_profit_margins to evaluate profitability, optimize_pricing_mix to find the best price points, and get_modality_impact_summary to see how different modalities contribute to the total cost.

multi-modalpricingcost-analysisai-economicsmargin-optimization

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

analyze_profit_margins

Evaluates the profitability of a specific pricing model

calculate_request_cost

Determines the total cost of a single multi-modal request

get_modality_impact_summary

Provides a summary of how much each modality contributes to the total cost

optimize_pricing_mix

Recommends the best pricing structure to maximize profit

See how to talk to your AI agent using Multi-Modal AI Economics Engine.

Calculate the cost for a request with 1000 text tokens, 2 images, and a $0.01 unit cost for text and $0.10 for images, with multi-modal fusion enabled.

The total cost for the request is $0.12, which includes $0.01 for text, $0.20 for images, and the applicable fusion overhead.

What is the profit margin if a request costs $0.50 and I charge the user $1.25 with a volume of 1000 requests?

The gross profit is $0.75 per request, resulting in a 60% margin and a total expected profit of $750.00.

Recommend a price for a service with a base cost of $0.40, a target margin of 40%, and a competitor price of $0.60.

The recommended price is $0.60, following a Competitive-Driven strategy to match the market while maintaining viability.

The engine uses `calculate_request_cost` to add a specific fusion overhead when multiple modalities are detected in a single request, ensuring the computational cost of aligning inputs is captured.

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