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Portfolio Concentration Calculator

Portfolio Concentration Calculator MCP Connector for Claude

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Measure investment risk using the Herfindahl-Hirschman Index (HHI) across asset, sector, and geography dimensions.

3 tools Official Updated Jun 28, 2026 Official Vinkius Partner
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This MCP server provides a specialized engine for analyzing portfolio diversification. By using the calculate_concentration_metrics tool, you can compute the Herfindahl-Hirschman Index (HHI) to identify concentration risks within your holdings at the asset, sector, and geography levels. The server also includes get_diversification_recommendation to provide actionable advice on rebalancing highly concentrated dimensions and validate_portfolio_data to ensure your input data is mathematically sound for HHI calculations.

hhiportfoliodiversificationinvestmentrisk

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

calculate_concentration_metrics

Calculates HHI and concentration metrics

get_diversification_recommendation

Gets diversification recommendations

validate_portfolio_data

Validates the input portfolio data

See how to talk to your AI agent using Portfolio Concentration Calculator.

Calculate the concentration metrics for a portfolio with 50% Apple (Tech, USA), 30% Microsoft (Tech, USA), and 20% Tesla (Auto, USA).

The analysis shows a high concentration in the Technology sector (HHI: 0.34) and the USA geography (HHI: 1.0). The Sector rating is 'Concentrated'.

What should I do to diversify my portfolio if my sector concentration is too high?

To reduce risk, you should redistribute weight from your most concentrated sectors into underrepresented industries like Healthcare or Energy.

Check if my portfolio data is valid: [{'weight': 0.5, 'sector': 'Tech', 'geography': 'USA'}, {'weight': -0.1, 'sector': 'Energy', 'geography': 'UK'}]

The validation failed because the asset with weight -0.1 has an invalid negative value.

The HHI is a standard economic metric used to measure market or portfolio concentration. It is calculated by squaring the weight of each component and summing the results.

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