BMI Kit

What BMI Kit MCP server does

BMI Kit MCP server brings several body-composition measurements into an MCP-accessible interface. The listed capabilities include BMI, body-fat percentage, fat-free mass index (FFMI), and waist-to-height ratio. It also includes saved measurement trends, so the service covers both individual calculations and previously stored measurement data.

The source listed for the project is https://bmikit.com/mcp. Based on the available description, the intended use is to let AI agents request body-composition results through BMI Kit rather than requiring an agent to implement each calculation independently.

How it works

An MCP-compatible client can use BMI Kit’s exposed capabilities for the metrics named in the listing. A request may concern a current body-composition calculation, or it may involve saved measurement trends. The available material does not define the tool names, parameter names, accepted units, response format, or whether trend queries support filtering or date ranges.

BMI Kit MCP server is therefore best evaluated for use cases that need the four stated metrics or access to stored measurement history. The listing does not provide enough technical detail to describe the calculation formulas, required inputs, data retention behavior, or handling of incomplete measurements.

Limitations and notes

The README is unavailable, so setup and operational details cannot be confirmed from the supplied material. No environment variables, authentication method, package name, launch command, transport type, or configuration file are documented here. Client-specific support is also unspecified.

The description identifies body-composition calculations and saved trends, but it does not state whether BMI Kit offers medical interpretation, recommendations, diagnosis, alerts, exports, or synchronization with another health platform. Those capabilities should not be assumed.

Before deployment, verify how the BMI Kit MCP server is started, how an MCP client connects to the /mcp endpoint, which inputs each operation accepts, and how saved measurements are authorized and retrieved. Also confirm whether the service is appropriate for the sensitivity of the body-composition data handled by the intended workflow.