searchloinc
Enables LLMs to search LOINC terms with free-text, relevance-ranked, and faceted queries via the LOINC Search API, mirroring the loinc.org/search experience.
README
SearchLOINC
A thin MCP server wrapping the
LOINC Search API so LLMs can search LOINC the same
way a human does via loinc.org/search — free-text,
relevance-ranked, faceted. It targets the documented Search API
(https://loinc.regenstrief.org/searchapi/), not the FHIR terminology service.
Setup
uv sync --extra dev
cp .env.example .env # then fill in your LOINC credentials
Credentials come from a free registration on loinc.org. Set
LOINC_USERNAME and LOINC_PASSWORD in the environment (never commit them).
Run
From a checkout (development):
uv run python -m searchloinc
Or install it as a standalone command and run it from anywhere:
uv tool install . # puts a `searchloinc` executable on PATH
searchloinc # starts the stdio server
Both run the server over stdio (the transport MCP clients expect). Point your client at
the command, or add it to your client's MCP server config. When you use the installed command,
supply credentials through the client's env block (sourced from your secret store / shell —
never committed):
{
"mcpServers": {
"searchloinc": {
"command": "searchloinc",
"env": {
"LOINC_USERNAME": "your-loinc-username",
"LOINC_PASSWORD": "your-loinc-password"
}
}
}
}
The checked-in .mcp.json uses the dev form (uv run --env-file .env) so a local
checkout picks up credentials from .env automatically.
Tools
Two-tier design — cheap compact search for triage, explicit drill-in for detail:
search_loincs— LOINC terms (lab tests, vitals, measurements, panels, surveys). The main table.search_answerlists— enumerated answer sets attached to survey/nominal terms.search_parts— the LP-coded building blocks (components, systems, methods, properties).search_groups— curated collections of related terms.get_loinc(code)— drill into one term by exact code; returns the full flat record.
Each search tool takes query (required), rows, offset, sortorder, language, and
include_facets. Pick the scope that matches what you're after; results are
relevance-ranked, so if the top hits miss, reformulate rather than deep-page. Triage with
a search tool, then get_loinc the code you want.
Output shape
Search responses are a JSON envelope plus a result table:
- The table is serialized as TOON — a compact tabular
format that pays the column-name cost once, so wide uniform tables stay small. Columns are
fixed per scope; empty fields render as
""to preserve row uniformity. Tab-delimited (LOINC display values contain commas but never tabs). - The envelope reports
requested,returned,total,offset, andtruncated.
Character budget & pagination. The whole serialized payload is capped at 9500 characters
(a cushion under the ~10K downstream tool-result limit). The row-packing loop encodes and
measures the full payload incrementally and stops before the cap; when results don't all fit,
truncated is true — page forward with offset. include_facets (filter counts) is off by
default and opt-in; facet payloads still respect the budget.
get_loinc returns a single JSON object — the flat search-API record with null/empty fields
dropped (always keeping Link), so the field set adapts to the term type. Page-only content
(part LP hierarchy, language variants, curated part descriptions) is not in the flat
record — follow Link to loinc.org for it.
There is a debug-only raw-JSON path toggled by the SEARCHLOINC_RAW_JSON env var; it is never
exposed as an agent-facing tool parameter.
Development
uv run ruff check searchloinc # lint
uv run pytest # tests (no network; API stubbed with fixtures)
The /loinc-search skill drives the live API to
validate wrapper output against ground truth.
Status
Wrapper is implemented and validated against the live API. Eventual deployment target is a Databricks app (credentials via secret scope, inference via AI Gateway).
License & attribution
The SearchLOINC code is licensed under the MIT License.
This project wraps the LOINC Search API and includes sample LOINC API responses as test fixtures. That LOINC (and referenced SNOMED CT) content is not covered by the MIT license and remains under its own terms — see NOTICE for the required attributions.
This material contains content from LOINC (http://loinc.org). LOINC is copyright © Regenstrief Institute, Inc. and the Logical Observation Identifiers Names and Codes (LOINC) Committee and is available at no cost under the license at http://loinc.org/license. LOINC® is a registered United States trademark of Regenstrief Institute, Inc.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.