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MCP server for Open Masala — ancestry-adjusted health reference ranges (South Asian biomarker cutoffs, cited).

Project description

Open Masala MCP server

An ancestry-adjusted health reference oracle over the Open Masala dataset, exposed via the Model Context Protocol so any MCP client — Claude Desktop, Claude Code, an agent — can query cited, provenance-tiered reference values as tool calls.

Design principle: it holds no user data

The server is a stateless reference oracle. Tools like evaluate_value take a value as an argument and return a computed, cited result — nothing is stored, and no personal data ever lives here. All handling of a person's actual labs happens in the client / advisor layer (see ../advisor/), never in this server. That's what makes it safe to publish and run anywhere.

Tools

Tool What it does
list_measures() Every analyte/measure in the dataset — the coverage map. Start here.
get_reference(analyte) Ancestry-adjusted range(s)/threshold(s) for an analyte, paired with the general-population value, provenance tier, grade, citations, and overclaim guard. Matches a LOINC code, id, or name.
evaluate_value(analyte, value, sex?, age?) Compare a person's own value against the South-Asian-adjusted threshold; returns a flag status + cited rationale + overclaim guard. Stateless.
screening_for(age, sex?) Which SA-specific screenings/thresholds apply to a person of this age/sex. Cited.
search(query) Free-text search across analytes, notes, guards, and sources.
list_sources() Every unique citation backing the dataset.

Resources

  • open-masala://dataset — the full canonical JSON.
  • open-masala://guidance — the provenance-tier + overclaim usage rules a client should follow.

Install & run

No clone (recommended)uv fetches and runs it from PyPI:

uvx open-masala-mcp

From a source checkout:

pip install "mcp[cli]"
python3 mcp-server/server.py        # or: python -m open_masala_mcp.server

Add to Claude Desktop

Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "open-masala": {
      "command": "uvx",
      "args": ["open-masala-mcp"]
    }
  }
}

Restart Claude Desktop; the Open Masala tools appear in the tools menu. Now you can ask, e.g., "I'm a South Asian man, 34, BMI 24 — what does Open Masala say?" and Claude will call evaluate_value / screening_for and answer with cited, guard-respecting reference values.

(From a checkout instead of PyPI, use "command": "python3", "args": ["/absolute/path/to/open-masala/mcp-server/server.py"].)

Add to Claude Code

claude mcp add open-masala -- uvx open-masala-mcp

Responsible-use contract

Every tool response includes usage_rules and a disclaimer. Clients (and the LLMs driving them) should:

  • Report the provenance_tier — never present a study-derived value as guideline-backed, and tell the user not to apply a contested-deprecated adjustment.
  • Honor the overclaim_guard on every row.
  • Cite the sources attached to each row.
  • Defer diagnosis and treatment to a clinician.

This is a reference dataset, not a medical device.

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