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ACLM Lab Interpreter

rabyavalla/bonsai-api

You'd reach for this when you need to evaluate lab results against American College of Lifestyle Medicine optimized reference ranges rather than standard clinical ranges. It interprets lab values and flags deprescription opportunities, which is useful if you're building tools for preventive medicine, functional health practices, or medication reconciliation workflows. The source is light on implementation details, but the concept is straightforward: send in lab data, get back analysis based on ACLM standards that tend to be tighter than conventional ranges, plus signals about where medications might be reduced or eliminated. Hosted on Railway and accessible via streamable HTTP transport.

tools
2
transport
HTTP
last updated
May 30, 2026
View on GitHub

Install

From registry metadata
$ npx add-mcp https://web-production-ae61.up.railway.app/mcp/aclm-lab-interpreter --name aclm-lab-interpreter

Run in your terminal. add-mcp asks which agents to add it to (Claude Code, Codex, Cursor and more). Add -g to install it for every project.

Review the command, arguments and environment values before installing. MCP servers run with your local permissions.

Other ways

Claude Code

$ claude mcp add --transport http aclm-lab-interpreter https://web-production-ae61.up.railway.app/mcp/aclm-lab-interpreter

Run in your terminal. Add --scope user to make it available in every project.

Tools

Verified live · 2 tools

Verified live against the running server on Nov 6, 2026.

interpret_labsInterpret a panel of lab values against ACLM-optimized reference ranges. Returns risk classification per marker, lifestyle interventions, and medication deprescription signals.3 params

Interpret a panel of lab values against ACLM-optimized reference ranges. Returns risk classification per marker, lifestyle interventions, and medication deprescription signals.

Parameters* required
current_medicationsarray
health_goalsarray
lab_values*object
Key-value pairs of biomarker names and values. Common keys: hba1c, fasting_glucose, fasting_insulin, ldl, hdl, triglycerides, apob, lp_a, hscrp, vitamin_d, b12, ferritin, tsh, free_t4, free_t3.
marker_referenceLook up the ACLM-optimized reference range and lifestyle intervention plan for a single biomarker (e.g., apob, lp_a, hscrp, hba1c, fasting_insulin, vitamin_d).1 params

Look up the ACLM-optimized reference range and lifestyle intervention plan for a single biomarker (e.g., apob, lp_a, hscrp, hba1c, fasting_insulin, vitamin_d).

Parameters* required
marker*string

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Readme

Details

Repository
github.com/rabyavalla/bonsai-api
Transport
HTTP
Registry
MCP registry, active
Tools verified
Nov 6, 2026

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