io.github.SidneyBissoli/medical-terminologies-mcp

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Méthode : MCP Hub analyse la description de chaque outil (couche 1) et, pour le verdict fort, exécute le serveur dans une micro-VM isolée avec leurres et réseau bloqué (couche 2). On publie des noms et des compteurs, jamais le contenu brut renvoyé par un outil.

Les 33 outils

• atc_classify≈ 1807 tokens

  Look up the WHO ATC (Anatomical Therapeutic Chemical) classification(s) for a drug by name. Use this tool to: - Find the ATC code for a medication (e.g., "metformin" → A10BA02) - Identify the therapeutic and pharmacological class hierarchy - Cross-reference drugs with their international ATC codes Returns one entry per ATC code the drug belongs to. A single-ingredient drug typically maps to one substance-level code; combination products map to multiple. ATC codes are international (WHO Collaborating Centre); this tool retrieves them via NLM RxClass. Input is a drug NAME (brand or generic, English/US naming as in RxNorm). A name RxNorm does not recognize, or a drug without an ATC mapping, returns an empty `matches` list with an explanatory note — not an error; try the generic name, or resolve the name first with rxnorm_search. Which ATC tool: start here when you have a drug name; use atc_lookup when you already have a class code (level 1-4, e.g. "A10BA") and want its name; use atc_members to list the drugs inside a class.

  Paramètres, retour & exemple (1)

  Paramètres

  • drug_name · string · requis
    Drug name to classify (brand or generic, e.g., "metformin")

  Exemple d'appel

  {"name": "atc_classify", "arguments": {"drug_name": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"matches": [], "drug_name": "texte", "provenance": {}, "attribution": []}}

• atc_lookup≈ 1699 tokens

  Look up an ATC code at level 1-4 to get its name and hierarchy level. Use this tool to: - Resolve an ATC code (e.g., "A10BA") to its class name ("Biguanides") - Confirm a code exists in the current ATC index - Identify the level (anatomical / therapeutic / pharmacological / chemical) Accepts codes 1-5 characters long: "A" (anatomical), "A10" (therapeutic), "A10B" (pharmacological), "A10BA" (chemical). Substance-level codes (7 chars, e.g., "A10BA02") are not exposed by this endpoint — use atc_classify with the drug name to retrieve the substance code.

  Paramètres, retour & exemple (1)

  Paramètres

  • atc_code · string · requis
    ATC code at level 1-4 (1-5 chars). Substance-level codes (7 chars, e.g., A10BA02) are not exposed by this endpoint — use atc_classify with the drug name instead.

  Exemple d'appel

  {"name": "atc_lookup", "arguments": {"atc_code": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"found": true, "details": "texte", "atc_code": "texte", "provenance": {}, "attribution": []}}

• atc_members≈ 1664 tokens

  List the drugs (substances) that belong to an ATC class. Use this tool to: - Enumerate all members of a therapeutic class (e.g., "A10BA" → metformin, phenformin) - Build a list of drugs sharing a pharmacological mechanism - Explore an ATC subtree at any level Each member includes its substance-level (7-char) ATC code via source_atc_code, useful for disambiguation when the queried class is at level 1-4. RxNorm's catalog is US-centric; the ATC class names and codes themselves are international.

  Paramètres, retour & exemple (1)

  Paramètres

  • atc_code · string · requis
    ATC code at any level. Higher levels (1-4) return all member substances; level 5 returns the single substance.

  Exemple d'appel

  {"name": "atc_members", "arguments": {"atc_code": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"members": [], "atc_code": "texte", "provenance": {}, "attribution": []}}

• cid10_chapter≈ 1875 tokens

  Get one CID-10 chapter and its constituent groups (e.g., "Chapter IX → I00-I02 Febre reumática aguda, I05-I09 Doenças reumáticas crônicas do coração, ..."). Use this tool to: - Drill from a chapter into its groups (code ranges with Portuguese titles) - Build hierarchical browsers - Find which group contains a code range Provide the chapter number `num` as an integer 1-22 (chapter I = 1, IX = 9). Numbers outside 1-22 are rejected with a validation error. Returns the chapter (title and code range) plus ALL its groups in one response — no pagination; the 22 chapters hold 275 groups in total. Answered locally from the bundled CID-10 V2008; no network call. Which CID-10 tool: use cid10_chapters first if you do not know the chapter number (it lists all 22 with code ranges); use cid10_lookup for one specific code and cid10_search to find codes by Portuguese text. For the international ICD-11, use icd11_chapters.

  Paramètres, retour & exemple (1)

  Paramètres

  • num · integer · requis
    Chapter number (1-22). CID-10 V2008 has 22 chapters.

  Exemple d'appel

  {"name": "cid10_chapter", "arguments": {"num": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"num": 1, "found": true, "groups": [], "chapter": "texte", "provenance": {}, "attribution": []}}

• cid10_chapters≈ 1610 tokens

  List the 22 chapters of CID-10 with their code ranges and Portuguese titles. Use this tool to: - See the top-level structure of CID-10 (chapters I-XXII, e.g., "I. Algumas doenças infecciosas e parasitárias", "IX. Doenças do aparelho circulatório") - Map a code to its chapter by code range (e.g., I00-I99 → chapter IX) - Build a navigable table of contents for downstream tooling Returns 22 entries — CID-10 V2008 has not been updated since 2008.

  Paramètres, retour & exemple (0)

  Exemple d'appel

  {"name": "cid10_chapters", "arguments": {}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"chapters": [], "provenance": {}, "attribution": []}}

• cid10_lookup≈ 1763 tokens

  Look up a specific CID-10 code and return its Portuguese name. Use this tool to: - Resolve a code to its Brazilian description ("I21" → "Infarto agudo do miocárdio") - Confirm a 3-char category or 4-char subcategory exists in CID-10 - Retrieve gender / cause-of-death restriction flags when applicable Accepts both dotted ("A00.1") and undotted ("A001") forms; returns the canonical display.

  Paramètres, retour & exemple (1)

  Paramètres

  • code · string · requis
    CID-10 code (e.g., "A00", "A00.1", "A001", "I21"). Dotted and undotted forms both accepted.

  Exemple d'appel

  {"name": "cid10_lookup", "arguments": {"code": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"hit": "texte", "code": "texte", "found": true, "provenance": {}, "attribution": []}}

• cid10_search≈ 2085 tokens

  Search the Brazilian CID-10 (Classificação Estatística Internacional de Doenças, 10ª Revisão) by Portuguese text. Use this tool to: - Find CID-10 codes for Brazilian SUS / ANVISA contexts ("infarto", "diabetes", "tuberculose") - Look up the official Portuguese (CBCD/USP) translation of a clinical term - Locate codes for billing, epidemiology, and clinical documentation in Brazil Returns matches from CID-10 categories (3-char) and/or subcategories (4-char). Search is diacritic-insensitive: typing "infeccoes" matches "infecções". Every word must match (AND), and everyday Portuguese is resolved to the CID-10's own wording (câncer→neoplasia maligna, AVC→acidente vascular cerebral, pressão alta→hipertensão, suicídio→lesão autoprovocada, aids→HIV); when that happens the response says so in vocabulary_notes. This tool searches the Brazilian Portuguese CID-10 V2008 — for the international ICD-11 (current WHO revision, in English by default), use icd11_search.

  Paramètres, retour & exemple (3)

  Paramètres

  • level · string · optionnel · categories | subcategories | all
    Restrict search to 3-char categories, 4-char subcategories, or both. Default: all
  • query · string · requis
    Search terms in Portuguese, AND between words (e.g., "diabetes", "infarto", "câncer de mama"); accents ignored, everyday words resolved to CID-10 wording
  • max_results · integer · optionnel
    Maximum number of results (1-100). Default: 25

  Exemple d'appel

  {"name": "cid10_search", "arguments": {"query": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"hits": [], "level": "categories", "query": "texte", "provenance": {}, "attribution": [], "shown_count": 1, "total_count": 1, "vocabulary_notes": []}}

• fetch≈ 1760 tokens

  Returns the full document for an id obtained from `search`, as { id, title, text, url, metadata }: `text` is the readable content (Markdown) and `url` the canonical public page to cite. Companion of `search` in the OpenAI Deep Research contract, over the medical terminologies (CID-10 categories and chapters, ICD-11, LOINC, RxNorm, MeSH, terminology version records) catalog. Only ids returned by `search` are valid; an unknown id returns an error. The terminology tools (`icd11_*`, `cid10_*`, `loinc_*`, `rxnorm_*`, `mesh_*`, `atc_*`, `map_*`, `find_equivalent`, `validate_codes`) remain the tools for data queries. Behavior: read-only and idempotent — a live GET against the public source when the document needs it.

  Paramètres, retour & exemple (1)

  Paramètres

  • id · string · requis
    Identifier of a document returned by `search`

  Exemple d'appel

  {"name": "fetch", "arguments": {"id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"id": "texte", "url": "texte", "text": "texte", "title": "texte", "metadata": {}, "provenance": {}, "attribution": []}}

• find_equivalent≈ 2933 tokens

  Ranked unified search for equivalent terms across multiple medical terminologies. Use this tool to: - Find the same concept in different coding systems - Compare how terminologies represent a concept - Support terminology mapping and data integration Searches across: ICD-11, LOINC, RxNorm, and MeSH. Set `target_terminologies` to limit which are searched, or set `source_terminology` to exclude one (e.g. when you already have a code from that terminology and want equivalents elsewhere). The two combine: source is subtracted from targets. `limit` caps candidates per terminology (default 5, max 10). Every candidate carries `match_score` (lexical similarity to the search term, 0-1) and `rank` (global position across all searched terminologies) — both computed by this server, since upstreams don't expose comparable relevance scores. Candidates from different terminologies whose titles are lexically identical are clustered in `groups` — a strong same-concept signal (absence of a group is NOT evidence of non-equivalence). Searches upstreams in English. For official pt-BR content, use the dedicated tools: `icd11_search`/`mesh_search` accept `language: "pt"`, and `cid10_search` is natively Portuguese.

  Paramètres, retour & exemple (4)

  Paramètres

  • term · string · requis
    Medical term to search (e.g., "diabetes", "aspirin")
  • limit · integer · optionnel
    Maximum candidates returned PER terminology (1-10, default 5). This is a cap, not a page: the live fan-out has no stable cursor across five upstreams, so raise the limit instead of paging.
  • source_terminology · string · optionnel · icd11 | loinc | rxnorm | mesh
    If set, this terminology is excluded from the search. Use this when the term came from this terminology and you want equivalents in the others. Combines with target_terminologies by subtraction (source is removed from the target list).
  • target_terminologies · array · optionnel
    Limit the search to these terminologies. If omitted, all five are searched.

  Exemple d'appel

  {"name": "find_equivalent", "arguments": {"term": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"term": "texte", "groups": [], "ranking": {}, "results": {}, "provenance": [], "attribution": [], "source_terminology": "texte", "searched_terminologies": []}}

• harmonize_terms≈ 3338 tokens

  Map a LIST of free-text clinical terms to standard codes in one call, with ranked candidates and a confidence label for each — the building block of a reviewable crosswalk. Use this tool to: - Harmonize a column of diagnoses, drugs or lab names from a dataset to ICD-11 / RxNorm (+ ATC) / LOINC - Triage which terms map cleanly (exact / strong) and which need a person (needs_review) - Build a crosswalk you can audit: every row keeps its candidates, scores and sources Give each term its `domain`: diagnosis → ICD-11; drug → RxNorm concepts (ingredients first) plus the ATC classes of the term; lab → LOINC. Up to 50 terms per call — a longer list is refused with a validation error: split it into batches of 50. Repeated term+domain pairs are looked up once. `max_candidates` keeps 1-5 per term (default 3). Every candidate carries `match_score` (lexical, 0-1, the find_equivalent formula) and `match_type`: exact = same words after normalization; strong = every term word is in the title (or the matched synonym) and score ≥ 0.85; needs_review = anything else. A one-word term is exact or needs_review, never strong ("Tylenol" vs "Tylenol PM" is a different product). Synonyms, abbreviations ("MI", "HbA1c") and misspellings land in needs_review or no_candidates — the label errs toward asking a person. Candidates sharing no word with the term are dropped, as are LOINC codes named "Deprecated". For diagnoses, a candidate is also scored against the synonyms WHO matched (e.g. "hypertension NOS" for Essential hypertension), reported in `matched_label`; postcoordinated clusters (codes with "/" or "&") are left out — build those with icd11_postcoordination. Lab names are ambiguous without specimen and property: "glucose" matches over a thousand LOINC codes, so write "glucose serum" or expect needs_review. One failed lookup does not fail the batch: that row comes back with status "error". Terms are searched in English and sent to the WHO and NLM APIs — de-identify the list first. For Brazilian Portuguese diagnoses use cid10_search; to check codes you already have, use validate_codes; for one term across every terminology, use find_equivalent. Record the vocabulary versions with the provenance blocks (one per source) and terminology_versions.

  Paramètres, retour & exemple (2)

  Paramètres

  • terms · array · requis
    Terms to harmonize, each with its domain. Up to 50 per call; repeated term+domain pairs are looked up once.
  • max_candidates · integer · optionnel
    Candidates kept per term, best first (1-5, default 3).

  Exemple d'appel

  {"name": "harmonize_terms", "arguments": {"terms": []}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"total": 1, "counts": {}, "ranking": {}, "results": [], "provenance": [], "attribution": [], "unique_lookups": 1}}

• icd11_chapters≈ 1802 tokens

  List all ICD-11 chapters (top-level categories) of the pinned WHO release. Use this tool to: - Get an overview of ICD-11 structure - Find which chapter covers a body system or condition type - Get chapter URIs to drill down with icd11_hierarchy (direction 'children') Returns 28 entries in one response, no pagination — chapters 01-26 plus the supplementary sections V (functioning) and X (extension codes) — each with number, code, title and URI. Each chapter is fetched separately from WHO; if one fetch fails, that entry keeps its URI and carries an `error` instead of a title, and the rest still come back. Set `language` for WHO's official translations (e.g. `language: "pt"`); the result is cached, so repeated calls are cheap. When NOT to use: to find a specific disease, use icd11_search; for the Brazilian CID-10 (ICD-10) chapters, use cid10_chapters.

  Paramètres, retour & exemple (1)

  Paramètres

  • language · string · optionnel · en | es | pt | fr | de | it | zh | ja
    Language code (default: en). Returns the source's OFFICIAL translation when it exists (e.g. 'pt' for official Portuguese); content is never machine-translated.

  Exemple d'appel

  {"name": "icd11_chapters", "arguments": {"language": "en"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"chapters": [], "provenance": {}, "attribution": []}}

• icd11_hierarchy≈ 1846 tokens

  Navigate the ICD-11 hierarchy to find parent or child entities. Use this tool to: - Find broader categories (parents) of a condition - Find specific subtypes (children) of a condition - Understand the classification structure Name the entity by `code` (a leaf code like "5A11", or a block range like "5A10-5A2Y" — blocks come back from 'parents' with an empty code and a code_range) or by `uri` (the URI any previous answer returned). Direction 'parents' returns ancestor categories, 'children' returns subcategories. ICD-10 codes (like "E11") are not ICD-11 codes: convert them first with map_icd10_to_icd11.

  Paramètres, retour & exemple (4)

  Paramètres

  • uri · string · optionnel
    Entity URI as returned by icd11_lookup, icd11_search or a previous icd11_hierarchy call
  • code · string · optionnel
    ICD-11 code (e.g., "BA00", "5A11") or block range (e.g., "5A10-5A2Y")
  • language · string · optionnel · en | es | pt | fr | de | it | zh | ja
    Language code (default: en). Returns the source's OFFICIAL translation when it exists (e.g. 'pt' for official Portuguese); content is never machine-translated.
  • direction · string · requis · parents | children
    Direction: "parents" for ancestors, "children" for subtypes

  Exemple d'appel

  {"name": "icd11_hierarchy", "arguments": {"direction": "parents"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"code": "texte", "entities": [], "direction": "parents", "provenance": {}, "attribution": []}}

• icd11_lookup≈ 2044 tokens

  Get detailed information about ONE ICD-11 entity you already have a code or URI for. Use this tool to: - Get the full definition of a disease - Retrieve coding notes, inclusions and exclusions - Get the official title and index terms (synonyms) Provide `code` (e.g., "BA00") or `uri` (any URI a previous answer returned) — at least one is required; calling with neither returns a validation error naming both. Set `language` for WHO's official translations (e.g. `language: "pt"` for official Portuguese). Returns a single entity (no pagination). A code WHO does not know comes back as a "not found" error, never an empty record. When NOT to use: to find a code from a disease name, use icd11_search first; to walk parents/children, use icd11_hierarchy; for an ICD-10 code (like "E11"), convert it with map_icd10_to_icd11 — ICD-10 codes are not ICD-11 codes.

  Paramètres, retour & exemple (3)

  Paramètres

  • uri · string · optionnel
    Full ICD-11 foundation URI
  • code · string · optionnel
    ICD-11 code (e.g., "BA00", "1A00")
  • language · string · optionnel · en | es | pt | fr | de | it | zh | ja
    Language code (default: en). Returns the source's OFFICIAL translation when it exists (e.g. 'pt' for official Portuguese); content is never machine-translated.

  Exemple d'appel

  {"name": "icd11_lookup", "arguments": {"uri": "texte", "code": "texte", "language": "en"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"uri": "texte", "code": "texte", "title": "texte", "block_id": "texte", "class_kind": "texte", "code_range": "texte", "definition": "texte", "exclusions": [], "inclusions": [], "provenance": {}, "attribution": [], "browser_url": "texte"}}

• icd11_postcoordination≈ 1796 tokens

  List the postcoordination axes WHO allows for one ICD-11 stem code (MMS linearization, pinned release). Postcoordination means attaching extra detail to a stem code — severity, laterality, anatomy, causing agent, etc. — to build a composite (cluster) code. Use this tool to: - See which axes a stem code accepts before building a composite code - Check which axes are REQUIRED vs optional - See whether an axis takes one or several values, and how many values it offers Provide an ICD-11 `code` (e.g., "BA00"). Returns one entry per axis with `axis_name`, `required`, `allow_multiple` and `value_count` — the count of allowed values, not the values themselves. A code with no postcoordination, or one WHO does not know, returns an empty `axes` list (not an error), so check the code with icd11_lookup if the list is unexpectedly empty. When NOT to use: this does not build or validate a composite code, and it does not list the allowed values; to get a code from a disease name, use icd11_search.

  Paramètres, retour & exemple (1)

  Paramètres

  • code · string · requis
    ICD-11 code to get postcoordination info for

  Exemple d'appel

  {"name": "icd11_postcoordination", "arguments": {"code": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"axes": [], "code": "texte", "provenance": {}, "attribution": []}}

• icd11_search≈ 1858 tokens

  Search for medical conditions, diseases, and health problems in ICD-11 (International Classification of Diseases, 11th Revision). Use this tool to: - Find ICD-11 codes for diagnoses - Search for diseases by name or keyword - Look up conditions in multiple languages Set `language` for WHO's official translations — e.g. `language: "pt"` searches and returns the official Portuguese (pt-BR) ICD-11 labels. Never machine-translated. Returns matching entities with codes, titles, and relevance scores.

  Paramètres, retour & exemple (3)

  Paramètres

  • query · string · requis
    Search text (disease name, symptom, or keyword)
  • language · string · optionnel · en | es | pt | fr | de | it | zh | ja
    Language code (default: en). Returns the source's OFFICIAL translation when it exists (e.g. 'pt' for official Portuguese); content is never machine-translated.
  • max_results · integer · optionnel
    Maximum number of results (1-100). Default: 25

  Exemple d'appel

  {"name": "icd11_search", "arguments": {"query": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"query": "texte", "entities": [], "provenance": {}, "attribution": [], "total_count": 1}}

• loinc_answers≈ 1786 tokens

  Get the list of valid answers for a LOINC questionnaire item. Use this tool to: - Find valid response options for survey questions - Get answer codes (LA…) for data entry validation - Get the item scores of scored instruments (e.g. PHQ-9: "Not at all" = 0 … "Nearly every day" = 3) Returns each answer with its LOINC answer code (LA…), text, display order and score (null when the list has none). A valid LOINC code without a defined answer list (e.g. a numeric lab such as 2339-0) returns an empty list; a code LOINC does not know returns a "not found" error. Only applicable to LOINC codes that represent questions with defined answer sets. For the questions of a whole questionnaire, use loinc_panels; to find a code by name, use loinc_search.

  Paramètres, retour & exemple (1)

  Paramètres

  • loinc_num · string · requis
    LOINC number (e.g., "2339-0")

  Exemple d'appel

  {"name": "loinc_answers", "arguments": {"loinc_num": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"answers": [], "loinc_num": "texte", "provenance": {}, "attribution": []}}

• loinc_details≈ 1650 tokens

  Get detailed information about a specific LOINC code. Use this tool to: - Get the full name and description of a LOINC code - Find the component, property, timing, and system - Check the scale type and method Provide a LOINC number in format "XXXXX-X" (e.g., "2339-0" for Glucose).

  Paramètres, retour & exemple (1)

  Paramètres

  • loinc_num · string · requis
    LOINC number (e.g., "2339-0")

  Exemple d'appel

  {"name": "loinc_details", "arguments": {"loinc_num": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"class": "texte", "status": "texte", "system": "texte", "property": "texte", "component": "texte", "loinc_num": "texte", "provenance": {}, "scale_type": "texte", "short_name": "texte", "attribution": [], "method_type": "texte", "time_aspect": "texte"}}

• loinc_panels≈ 1708 tokens

  Get the structure of a LOINC panel or form. Use this tool to: - See all tests included in a panel (e.g., CBC, metabolic panel) - Get the structure of assessment forms - Find related observations grouped together Returns the list of LOINC codes that make up the panel.

  Paramètres, retour & exemple (1)

  Paramètres

  • loinc_num · string · requis
    LOINC number (e.g., "2339-0")

  Exemple d'appel

  {"name": "loinc_panels", "arguments": {"loinc_num": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"panel": "texte", "loinc_num": "texte", "provenance": {}, "attribution": []}}

• loinc_search≈ 1802 tokens

  Search for laboratory tests, clinical observations, and measurements in LOINC (Logical Observation Identifiers Names and Codes). Use this tool to: - Find LOINC codes for lab tests (e.g., "glucose", "hemoglobin") - Search for clinical measurements and vital signs - Look up diagnostic observations Returns matching LOINC codes with names, components, and properties.

  Paramètres, retour & exemple (2)

  Paramètres

  • query · string · requis
    Search term (test name, keyword, or partial LOINC code)
  • max_results · integer · optionnel
    Maximum number of results (1-100). Default: 25

  Exemple d'appel

  {"name": "loinc_search", "arguments": {"query": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"items": [], "query": "texte", "provenance": {}, "attribution": [], "shown_count": 1, "total_count": 1}}

• map_icd10_to_icd11≈ 2298 tokens

  Authoritative ICD-10 → ICD-11 mapping using WHO transition tables (release 2025-01, bundled with the server). Returns the primary 1:1 ICD-11 category for the ICD-10 code plus any alternative ICD-11 candidates that WHO documents (some ICD-10 concepts split into multiple ICD-11 entities). For each mapping, includes the ICD-11 code, title, chapter, and the Foundation URI / Linearization URI for navigating to the full entity definition. Use this for clinical coding, billing migration, retrospective analysis, and any workflow that needs authoritative mapping rather than text-search candidates. Coverage: 11,243 ICD-10 categories (excludes chapters and blocks like "A00-A09" which aren't used in clinical coding). Provide a code like "E11" (Type 2 diabetes), "I21" (Acute MI), or "A07.8" (4 alternatives in WHO's table). Both dotted ("A07.8") and undotted ("A078") forms are accepted. Returns "no mapping" when the code isn't in the WHO category-level table — that's the honest answer rather than a fuzzy search fallback.

  Paramètres, retour & exemple (1)

  Paramètres

  • icd10_code · string · requis
    ICD-10 code to query in the ICD-11 search index (e.g., E11, I21.0, J18.9)

  Exemple d'appel

  {"name": "map_icd10_to_icd11", "arguments": {"icd10_code": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"found": true, "icd10": "texte", "query": "texte", "source": {}, "primary": "texte", "provenance": {}, "attribution": [], "alternatives": []}}

• mesh_descriptor≈ 1832 tokens

  Get detailed information about a MeSH descriptor by ID. Use this tool to: - Get the full definition (scope note) of a MeSH term - View tree numbers showing hierarchy location - See related concepts and synonyms Provide a MeSH Descriptor ID like "D015242" (Ofloxacin). Set `language` to request NLM's official translations where they exist (e.g. `language: "pt"`).

  Paramètres, retour & exemple (2)

  Paramètres

  • mesh_id · string · requis
    MeSH Descriptor ID (e.g., D015242, D003920)
  • language · string · optionnel · en | es | pt | fr | de | it | zh | ja
    Language code (default: en). Returns the source's OFFICIAL translation when it exists (e.g. 'pt' for official Portuguese); content is never machine-translated.

  Exemple d'appel

  {"name": "mesh_descriptor", "arguments": {"mesh_id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"id": "texte", "uri": "texte", "label": "texte", "concepts": [], "provenance": {}, "qualifiers": [], "scope_note": "texte", "attribution": [], "tree_numbers": []}}

• mesh_qualifiers≈ 1574 tokens

  Get allowed qualifiers (subheadings) for a MeSH descriptor. Use this tool to: - Find which qualifiers can be combined with a descriptor - Build precise MeSH search queries - Understand aspects that can be specified Qualifiers refine descriptors (e.g., "Diabetes Mellitus/drug therapy").

  Paramètres, retour & exemple (1)

  Paramètres

  • mesh_id · string · requis
    MeSH Descriptor ID (e.g., D015242, D003920)

  Exemple d'appel

  {"name": "mesh_qualifiers", "arguments": {"mesh_id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"mesh_id": "texte", "provenance": {}, "qualifiers": [], "attribution": []}}

• mesh_search≈ 1805 tokens

  Search for MeSH (Medical Subject Headings) descriptors. Use this tool to: - Find MeSH terms for indexing medical literature - Look up subject headings for PubMed searches - Find controlled vocabulary terms Set `language` to request NLM's official translations where they exist (e.g. `language: "pt"` for Portuguese labels); content is never machine-translated. Returns matching descriptors with MeSH IDs and labels.

  Paramètres, retour & exemple (4)

  Paramètres

  • match · string · optionnel · exact | contains | startswith
    Match type: exact, contains, or startswith. Default: contains
  • query · string · requis
    Search term (e.g., "diabetes", "heart failure")
  • language · string · optionnel · en | es | pt | fr | de | it | zh | ja
    Language code (default: en). Returns the source's OFFICIAL translation when it exists (e.g. 'pt' for official Portuguese); content is never machine-translated.
  • max_results · integer · optionnel
    Maximum number of results (1-100). Default: 25

  Exemple d'appel

  {"name": "mesh_search", "arguments": {"query": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"match": "exact", "query": "texte", "provenance": {}, "attribution": [], "descriptors": [], "total_count": 1}}

• mesh_tree≈ 1570 tokens

  Get the tree hierarchy location(s) for a MeSH descriptor. Use this tool to: - See where a term fits in the MeSH hierarchy - Understand broader/narrower relationships - Find related terms in the same branch MeSH tree numbers show the hierarchical path (e.g., C14.280.647 for Myocardial Infarction).

  Paramètres, retour & exemple (1)

  Paramètres

  • mesh_id · string · requis
    MeSH Descriptor ID (e.g., D015242, D003920)

  Exemple d'appel

  {"name": "mesh_tree", "arguments": {"mesh_id": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"mesh_id": "texte", "provenance": {}, "attribution": [], "tree_numbers": []}}

• rxnorm_classes≈ 1595 tokens

  Get therapeutic and pharmacologic classes for a drug. Use this tool to: - Find the drug class (e.g., "Beta-blockers", "NSAIDs") - Identify therapeutic categories - Look up mechanism of action classifications Returns class IDs, names, and classification sources.

  Paramètres, retour & exemple (1)

  Paramètres

  • rxcui · ? · requis
    RxCUI of the drug

  Exemple d'appel

  {"name": "rxnorm_classes", "arguments": {"rxcui": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"rxcui": "texte", "classes": [], "provenance": {}, "attribution": []}}

• rxnorm_concept≈ 1897 tokens

  Get detailed information about a specific RxNorm concept by RxCUI. Use this tool to: - Get the full name and synonyms for a drug - Check the concept status (active, remapped, etc.) - View related concepts (ingredients, brands, forms) Provide an RxCUI (RxNorm Concept Unique Identifier) like "161" — as a string of digits or as an integer.

  Paramètres, retour & exemple (2)

  Paramètres

  • rxcui · ? · requis
    RxNorm Concept Unique Identifier (string of digits or integer, e.g. "161" or 161)
  • include_related · ? · optionnel
    Include related concepts (ingredients, brands, dose forms). Default false; true/false, also accepted as the strings "true"/"false"

  Exemple d'appel

  {"name": "rxnorm_concept", "arguments": {"rxcui": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"tty": "texte", "name": "texte", "found": true, "rxcui": "texte", "status": "texte", "synonym": "texte", "umlscui": "texte", "language": "texte", "suppress": "texte", "provenance": {}, "attribution": [], "remapped_to": []}}

• rxnorm_ingredients≈ 1588 tokens

  Get active ingredients for a drug by RxCUI. Use this tool to: - Find the active ingredients in a medication - Check for single vs. multiple ingredient products - Identify the generic components of brand drugs Returns ingredient RxCUIs and names.

  Paramètres, retour & exemple (1)

  Paramètres

  • rxcui · ? · requis
    RxCUI of the drug

  Exemple d'appel

  {"name": "rxnorm_ingredients", "arguments": {"rxcui": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"rxcui": "texte", "provenance": {}, "attribution": [], "ingredients": []}}

• rxnorm_ndc≈ 1615 tokens

  Map between RxNorm concepts and National Drug Codes (NDC). Use this tool to: - Get all NDC codes for a drug (by RxCUI) - Find the RxCUI for an NDC code - Cross-reference between coding systems Provide either an RxCUI to get NDCs, or an NDC to get the RxCUI.

  Paramètres, retour & exemple (2)

  Paramètres

  • ndc · string · optionnel
    NDC code to look up RxCUI (alternative to rxcui)
  • rxcui · ? · optionnel
    RxCUI to get NDC codes for

  Exemple d'appel

  {"name": "rxnorm_ndc", "arguments": {"ndc": "texte", "rxcui": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"ndc": "texte", "ndcs": [], "rxcui": "texte", "provenance": {}, "query_mode": "ndcs_for_rxcui", "attribution": []}}

• rxnorm_search≈ 1646 tokens

  Search for drugs in RxNorm (Normalized names for clinical drugs). Use this tool to: - Find drug concepts by brand or generic name - Look up medications for prescribing - Search for drug formulations Returns matching drugs with RxCUI identifiers, names, and term types.

  Paramètres, retour & exemple (2)

  Paramètres

  • query · string · requis
    Drug name to search (brand or generic)
  • max_results · integer · optionnel
    Maximum number of results (1-100). Default: 25

  Exemple d'appel

  {"name": "rxnorm_search", "arguments": {"query": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"drugs": [], "query": "texte", "provenance": {}, "attribution": [], "total_count": 1}}

• search≈ 1895 tokens

  Searches the medical terminologies (CID-10 categories and chapters, ICD-11, LOINC, RxNorm, MeSH, terminology version records) catalog and returns up to 10 matching documents as { id, title, url }, ordered by relevance (an empty list means nothing matched). This tool exists for the OpenAI Deep Research contract: ChatGPT deep research, company knowledge and research workflows over the Responses API require exactly the tools `search` and `fetch`. Pass one of the returned ids to `fetch` to read the document. For direct questions and for data (values, series, rankings) prefer the terminology tools (`icd11_*`, `cid10_*`, `loinc_*`, `rxnorm_*`, `mesh_*`, `atc_*`, `map_*`, `find_equivalent`, `validate_codes`), which return the actual data with provenance — this is a catalog index, not a data query. Query: natural language or keywords, Portuguese or English; accents and case are ignored. Behavior: read-only and idempotent — the catalog comes from the public source and is cached in memory.

  Paramètres, retour & exemple (1)

  Paramètres

  • query · string · requis
    Search terms, natural language or keywords (accents and case are ignored)

  Exemple d'appel

  {"name": "search", "arguments": {"query": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"results": [], "provenance": [], "attribution": []}}

• terminology_diff≈ 2182 tokens

  Report what diff data is available between two versions of a terminology. For most terminologies this is **guidance only** — the server doesn't ship historical snapshots, so the tool points at the publisher's official changelog and explains the cadence. `bundled_versions` lists the version(s) this server actually has on hand. For **ICD-10 vs ICD-11** specifically, the tool surfaces a real cross-revision summary from the bundled WHO transition tables (the ICD-10 → ICD-11 case is a structural diff between two WHO revisions). Use `terminology: "icd10"` with no `to_version` to get the cross-revision summary: total mapped ICD-10 categories, how many are 1:1 vs split into multiple ICD-11 codes, and the average number of alternatives when split. Inputs: - `terminology` (required): which terminology to report on. - `from_version` (optional): the version you have data from. If omitted, the tool reports against the currently-bundled version. - `to_version` (optional): the version you want to compare to. If omitted, the tool reports against the publisher's latest known release. This tool is intentionally a metadata + guidance layer, not a diff engine — for terminologies that change frequently (LOINC, RxNorm, MeSH), the publisher's official changelog is the authoritative source.

  Paramètres, retour & exemple (3)

  Paramètres

  • to_version · string · optionnel
    Version you want to compare to. Optional.
  • terminology · string · requis · icd11 | icd10 | loinc | rxnorm | mesh | atc | cid10
    Which terminology to report on.
  • from_version · string · optionnel
    Version you have data from. Optional; behavior depends on terminology.

  Exemple d'appel

  {"name": "terminology_diff", "arguments": {"terminology": "icd11"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"message": "texte", "provenance": {}, "to_version": "texte", "attribution": [], "terminology": "icd11", "from_version": "texte", "changelog_url": "texte", "diff_available": true, "bundled_versions": [], "cross_revision_summary": "texte"}}

• terminology_versions≈ 1851 tokens

  List the current version, release date, publisher, source URL, and update cadence of every terminology this server queries against. Useful for pipeline maintainers who need to: - Confirm which release of ICD-11 / LOINC / RxNorm / MeSH / ATC the server is querying before a batch run. - Verify the bundled CID-10 (frozen at V2008) and ICD-10 → ICD-11 transition tables (currently 2025-01) match expectations. - Cite the data version in research artifacts. Pass `terminology` to filter to a single entry; otherwise the full set of 7 is returned. The ICD-10 → ICD-11 version reads live from the bundled dataset; everything else is metadata maintained alongside the project release.

  Paramètres, retour & exemple (1)

  Paramètres

  • terminology · string · optionnel · icd11 | icd10 | loinc | rxnorm | mesh | atc | cid10
    Filter to a single terminology. Omit to return all 7.

  Exemple d'appel

  {"name": "terminology_versions", "arguments": {"terminology": "icd11"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"total": 1, "generated": "texte", "provenance": {}, "attribution": [], "terminologies": []}}

• validate_codes≈ 2602 tokens

  Validate a mixed batch of medical codes against their source terminologies. Useful for retrospective analysis of legacy databases — flag codes that no longer exist, surface ICD-10 → ICD-11 replacements, and grade activity status where the terminology exposes it. For each input `{ code, terminology }`, returns: - **valid**: whether the code exists in the source terminology. - **active**: whether the code is currently active. Null when the source doesn't expose an explicit active/inactive distinction at category level (CID-10, ATC, ICD-11, RxNorm, MeSH all return null today; LOINC returns a real boolean). - **title**: the official label/name when available. - **replaced_by**: a successor code, populated today only for ICD-10 codes that have a primary ICD-11 mapping in the bundled WHO transition tables. - **source**: human-readable provenance of the validation (terminology + release/version). - **error**: non-null only when validation couldn't be performed (network error, upstream outage, etc.). `valid: false` + `error: null` means "code not found"; `valid: false` + `error: set` means "couldn't validate". Terminology is **required per code** — auto-detection isn't supported because category codes like "A00" exist in both ICD-10 and CID-10. Accepted values: `icd11`, `icd10`, `loinc`, `rxnorm`, `mesh`, `atc`, `cid10`. Hard cap of 50 codes per call; codes are validated in parallel through their respective clients, so total wall time scales with the slowest upstream + its rate limit (worst case ~10 s for a full batch hitting ICD-11).

  Paramètres, retour & exemple (1)

  Paramètres

  • codes · array · requis
    List of code+terminology pairs to validate. Hard cap of 50 per call to keep total latency under ~10 s given upstream rate limits.

  Exemple d'appel

  {"name": "validate_codes", "arguments": {"codes": []}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}], "structuredContent": {"total": 1, "results": [], "provenance": [], "attribution": [], "error_count": 1, "valid_count": 1, "invalid_count": 1}}

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Source

https://medical.sidneybissoli.com/mcp