ACLM Lab Interpreter

Official2 toolsLive

by rabyavalla

Interpret lab values against ACLM-optimized ranges. Returns deprescription signals.

The server interprets lab values against ACLM-optimized ranges and returns deprescription signals, enabling automated evaluation of medication suitability based on lab data.

🛠️ Key Features

Interprets lab values against ACLM-optimized ranges
Returns deprescription signals
Lightweight, with 2 tools available

🚀 Use Cases

Medical workflows requiring ACLM-aligned lab interpretation
Automated deprescription decision support
Integration with clinician dashboards and EHR systems

⚡ Developer Benefits

Clear, minimal API footprint with concise outputs
Straightforward integration for lab-value causality checks
GitHub-style repository clarity for maintenance

⚠️ Limitations

Limited tooling (2 tools)
Description based on provided data; no broader feature guarantees

Captured live from the server via tools/list.

interpret_labs

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

Parameters3

lab_values	object	required	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.
current_medications	array	optional
health_goals	array	optional

Raw schema

{
  "type": "object",
  "properties": {
    "lab_values": {
      "type": "object",
      "description": "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."
    },
    "current_medications": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "health_goals": {
      "type": "array",
      "items": {
        "type": "string"
      }
    }
  },
  "required": [
    "lab_values"
  ]
}

marker_reference

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).

Parameters1

marker

string

required

Raw schema

{
  "type": "object",
  "properties": {
    "marker": {
      "type": "string"
    }
  },
  "required": [
    "marker"
  ]
}

Install

Tools (2)

interpret_labsmarker_reference

Remote endpoint

Streamable HTTP

Hosted server - connect over the network, no local install.

url

https://web-production-ae61.up.railway.app/mcp/aclm-lab-interpreter

Add to VS Code Add to Cursor

claude_desktop_config.json

json

{
  "mcpServers": {
    "aclm-lab-interpreter": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://web-production-ae61.up.railway.app/mcp/aclm-lab-interpreter"
      ]
    }
  }
}

Desktop config is stdio-only; this bridges via mcp-remote. Native remote: Settings > Connectors.