Heor Agent

neptun2000/heor-agent-mcp

Brings pharmaceutical-grade health economics workflows into Claude as MCP tools. You get literature search across 44 sources (PubMed, NICE, ICER), automated risk-of-bias assessment using RoB 2 and ROBINS-I frameworks, cost-effectiveness modeling with EQ-5D value sets, and HTA dossier generation for NICE, FDA, EMA, and EU JCA submissions. The pharmacovigilance classifier maps studies to EMA regulatory categories and GVP modules in under 200ms. Includes workflow orchestrators for MAIC pipelines and IRB review prep. Built for pharma, biotech, and CRO teams who need auditable HEOR outputs without standing up custom infrastructure. Ships with JSON examples for complex tools and an AI transparency disclosure system aligned with ISPOR ELEVATE-GenAI guidelines.

GitHub stars: 11
tools: 31
transport: STDIO
last updated: Jul 4, 2026

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Tools

31 tools

Public tool metadata for what this MCP can expose to an agent.

literature.searchSearch PubMed, ClinicalTrials.gov, bioRxiv/medRxiv, ChEMBL, FDA Orange Book, FDA Purple Book, enterprise sources (Embase, ScienceDirect, Cochrane, Citeline, Pharmapendium, Cortellis), HTA cost reference sources (CMS NADAC, PSSRU, NHS National Cost Collection, BNF, PBS Schedule...8 params

Search PubMed, ClinicalTrials.gov, bioRxiv/medRxiv, ChEMBL, FDA Orange Book, FDA Purple Book, enterprise sources (Embase, ScienceDirect, Cochrane, Citeline, Pharmapendium, Cortellis), HTA cost reference sources (CMS NADAC, PSSRU, NHS National Cost Collection, BNF, PBS Schedule...

Parameters* required

date_fromstring

Exclude results before this date (ISO format: YYYY-MM-DD)

max_resultsnumber

Maximum results to return (default: 20, max: 100)

output_formatstring

Output format. 'docx' requires hosted tier.one of text · json · docx

projectstring

Project ID for knowledge base persistence. When set, results are saved to ~/.heor-agent/projects/{project}/raw/literature/

querystring

Research question (e.g. 'semaglutide type 2 diabetes cost-effectiveness')

runsnumber

Number of search runs (1-5, default 1). Multiple runs deduplicate and rank by consistency. Use runs=3 for comprehensive, stable results.

sourcesarray

Data sources to query. Default: pubmed, clinicaltrials, biorxiv, chembl, wiley, embase. Use 'who_gho' and 'world_bank' for epidemiology and demographic data. Use 'oecd' for OECD health statistics (...

study_typesarray

Filter results by study design. Values: 'rct' (randomised controlled trials), 'meta_analysis', 'observational' (cohort/case-control/cross-sectional), 'review' (systematic reviews, narrative reviews).

models.cost_effectivenessBuild a cost-utility analysis (ICER, QALY, PSA, sensitivity analysis) for a drug vs comparator. Follows ISPOR good practice guidelines and NICE reference case. Includes probabilistic sensitivity analysis (PSA), one-way sensitivity, and cost-effectiveness acceptability curve (C...18 params

Build a cost-utility analysis (ICER, QALY, PSA, sensitivity analysis) for a drug vs comparator. Follows ISPOR good practice guidelines and NICE reference case. Includes probabilistic sensitivity analysis (PSA), one-way sensitivity, and cost-effectiveness acceptability curve (C...

Parameters* required

clinical_inputsobject

Clinical efficacy and safety parameters driving the Markov transitions.

comparatorstring

Comparator (standard of care)

cost_inputsobject

Annual costs per patient in the base currency for the selected perspective.

indicationstring

Disease or condition

interventionstring

Drug or treatment name

mfn_sensitivityobject

Optional MFN price-sensitivity sweep. When supplied, the output includes an mfn_sensitivity block with ICER per price point and WTP-crossover prices. Design log #27.

model_typestring

Model type. Default: markov. Use 'partsa' for oncology — requires survival_inputs (the handler now hard-fails when partsa is set without it).one of markov · partsa · decision_tree

output_formatstring

Use 'xlsx' for a structured Excel report with inputs, transition matrix, PSA iterations, and CEAC in separate tabs. The workbook is a REPORT — editing cells does not re-run the model. Re-run by cal...one of text · json · docx · xlsx

perspectivestring

Economic perspective: 'nhs' (UK NHS, WTP £25-35K/QALY), 'us_payer' ($100-150K/QALY ICER standard), or 'societal' (broader costs incl. productivity).one of nhs · us_payer · societal

projectstring

Project ID for knowledge base persistence. When set, model run is saved to ~/.heor-agent/projects/{project}/raw/models/

psa_iterationsnumber

PSA iterations (default: 1000, max: 10000)

run_owsaboolean

Run one-way sensitivity analysis (default: true). Set to false to skip OWSA and speed up large PSA runs.

run_psaboolean

Run probabilistic sensitivity analysis (default: true)

scenariosarray

Optional scenario analysis: array of named parameter overrides. Each scenario re-runs the model with the specified changes. Max 10 scenarios.

summary_metricstring

Summary metric for the ICER numerator. 'qaly' (default, NICE reference case), 'evlyg' (equal value life-years gained — CMS IRA-compatible; CMS prohibits QALYs in Medicare IRA drug price negotiation...one of qaly · evlyg · both

survival_inputsobject

Required when model_type='partsa'. Median survival inputs (months) for OS/PFS, optional comparator overrides, and parametric distribution choice. Codex P1 fix (2026-05-07).

time_horizonstring

Modelling horizon: 'lifetime', '5yr', '10yr', or years as number

utility_inputsobject

QALY weights for each health state (optional — defaults derived from efficacy if omitted).

hta.dossierStructure evidence into HTA body-specific submission format (NICE STA, EMA, FDA, IQWiG, HAS, EU JCA, or Global Value Dossier). Produces draft sections with gap analysis and auto-GRADE evidence quality tables. Accepts output from literature.search and models.cost_effectiveness....18 params

Structure evidence into HTA body-specific submission format (NICE STA, EMA, FDA, IQWiG, HAS, EU JCA, or Global Value Dossier). Produces draft sections with gap analysis and auto-GRADE evidence quality tables. Accepts output from literature.search and models.cost_effectiveness....

Parameters* required

drug_namestring

Generic or brand name of the drug/intervention.

evidence_summaryvalue

Clinical evidence input. Accepts: a text summary string, OR a JSON array of LiteratureResult objects from literature.search (use output_format='json'). When passed as array, auto-generates a GRADE...

health_inequalitiesobject

Health inequalities evidence per NICE PMG36 May 2025 modular update. Required by NICE for interventions affecting disadvantaged groups. intervention_impact: 'narrows'/'neutral'/'widens'/'unknown'.

heterogeneity_per_outcomeobject

Optional: I² and study count per outcome (from evidence_indirect tool). When provided, GRADE inconsistency is computed from I² instead of heuristic. Example: { 'overall survival': { i_squared_pct:...

hta_bodystring

HTA body/dossier format. 'nice'=UK NICE STA; 'ema'=EMA CTD; 'fda'=FDA prescribing info; 'iqwig'=Germany AMNOG; 'has'=France transparency committee; 'jca'=EU Joint Clinical Assessment (Reg. 2021/228...one of nice · ema · fda · iqwig · has · jca

indicationstring

Disease or condition being treated (e.g., 'type 2 diabetes', 'non-small cell lung cancer').

mfn_contextobject

Optional MFN pricing context. When basket_prices is supplied and hta_body is one of {nice, ema, fda, iqwig, has, jca, gvd}, renders an MFN Exposure section with ceiling math and gap-to-US analysis....

model_resultsvalue

JSON output from models.cost_effectiveness — used to populate the Economic Evidence Summary section.

output_formatstring

Output format. 'text' returns markdown; 'json' returns structured sections; 'docx' generates a Word document and saves to disk.one of text · json · docx

picosarray

JCA-specific: list of PICOs from the scoping decision. Each PICO generates its own dossier section. If omitted, a default single PICO is generated.

projectstring

Project ID for knowledge base persistence. When set, dossier draft is saved to ~/.heor-agent/projects/{project}/raw/dossiers/

pv_classificationobject

Optional: structured PV classification from the pv_classify tool. When provided, the dossier includes a Pharmacovigilance Plan section with GVP module, ENCePP template, submission obligations, and...

regulatory_landscapearray

Optional: array of RegulatoryStatusResult objects from regulatory.status_check (via hta_workflow Phase 3.6). When provided and hta_body in {nice, jca, gvd}, renders a Regulatory Landscape section w...

rob_resultsvalue

Output from the evidence.risk_of_bias tool. When provided, the GRADE Risk of Bias domain uses the structured judgment (rob_judgment, downgrade, rationale) instead of a heuristic estimate.

severity_modifierobject

NICE PMG36 severity modifier inputs (replaced end-of-life modifier, April 2022). Provide absolute_qaly_shortfall (years) and/or proportional_qaly_shortfall (0-1). Modifier weight: <12 absolute AND...

submission_typestring

Submission type. 'sta'/'mta' for NICE; 'initial'/'renewal'/'variation' for JCA; 'early_access' for accelerated pathways.one of sta · mta · early_access · initial · renewal · variation

unmet_need_summarystring

Optional: 1-paragraph unmet need synthesis from the evidence.unmet_need tool. Pipe evidence.unmet_need result.unmet_need_summary here. Prepended to the Unmet Need section for NICE (Section B) and G...

upgrading_per_outcomeobject

Optional: GRADE upgrading flags per outcome for observational evidence (Guyatt 2011). Keys are outcome names; values specify large_effect ('none'/'large'/'very_large'), dose_response (boolean), and...

knowledge.searchSearch a project's knowledge base (raw/ and wiki/) for text matches. Returns file paths with line numbers and snippets. Use this to find previously-retrieved literature, model runs, and compiled wiki content without re-querying external APIs.5 params

Search a project's knowledge base (raw/ and wiki/) for text matches. Returns file paths with line numbers and snippets. Use this to find previously-retrieved literature, model runs, and compiled wiki content without re-querying external APIs.

Parameters* required

case_sensitiveboolean

Case-sensitive search (default false)

max_resultsnumber

Max matches to return (default 20, max 100)

pathsarray

Which subtrees to search. Default: both.

projectstring

Project ID (must exist)

querystring

Search query — multi-term searches match ANY term (OR)

knowledge.readRead a file from a project's raw/ or wiki/ tree. Path is relative to project root. Only raw/ and wiki/ subtrees accessible.2 params

Read a file from a project's raw/ or wiki/ tree. Path is relative to project root. Only raw/ and wiki/ subtrees accessible.

Parameters* required

pathstring

Relative path (e.g. 'wiki/trials/sustain-6.md' or 'raw/literature/pubmed_12345.md')

projectstring

Project ID

knowledge.writeWrite a file to the project's wiki/ tree. Path MUST start with 'wiki/' and end with '.md'. Use this to compile/organize evidence from raw/ files into a structured knowledge base. Supports Obsidian-style [[wikilinks]].3 params

Write a file to the project's wiki/ tree. Path MUST start with 'wiki/' and end with '.md'. Use this to compile/organize evidence from raw/ files into a structured knowledge base. Supports Obsidian-style [[wikilinks]].

Parameters* required

contentstring

Markdown content. Can include YAML frontmatter and [[wikilinks]].

pathstring

Relative path starting with 'wiki/', ending with .md (e.g. 'wiki/trials/sustain-6.md')

projectstring

Project ID

project.createInitialize a new HEOR project workspace with directory skeleton and project.yaml metadata. Idempotent — returns existing project if already created. Required before using the `project` parameter in other tools. Enum values are case-insensitive — `"NICE"`, `"Nice"`, and `"nice"...5 params

Initialize a new HEOR project workspace with directory skeleton and project.yaml metadata. Idempotent — returns existing project if already created. Required before using the `project` parameter in other tools. Enum values are case-insensitive — `"NICE"`, `"Nice"`, and `"nice"...

Parameters* required

drugstring

Drug or intervention name

hta_targetsarray

HTA bodies to target (optional). Case-insensitive — "NICE"/"Nice"/"nice" are all accepted.

indicationstring

Disease/condition being treated

notesstring

Free-text project notes (optional)

project_idstring

Short identifier (alphanumeric + hyphens, e.g. 'semaglutide-t2d')

evidence.networkAnalyze literature search results to build an evidence network map. Extracts intervention-comparator pairs from titles and abstracts, constructs a treatment comparison network, and assesses NMA (network meta-analysis) feasibility. Pass the results array from a prior literature...2 params

Analyze literature search results to build an evidence network map. Extracts intervention-comparator pairs from titles and abstracts, constructs a treatment comparison network, and assesses NMA (network meta-analysis) feasibility. Pass the results array from a prior literature...

Parameters* required

querystring

Original search query (optional, for context)

resultsarray

Array of LiteratureResult objects from a prior literature.search call (use output_format='json')

evidence.indirectCompute indirect treatment comparisons using the Bucher method (single common comparator) or frequentist network meta-analysis (full network). Requires user-supplied effect sizes (point estimates + 95% CI) from published trials. Supports MD, OR, RR, HR. Auto-selects method by...3 params

Compute indirect treatment comparisons using the Bucher method (single common comparator) or frequentist network meta-analysis (full network). Requires user-supplied effect sizes (point estimates + 95% CI) from published trials. Supports MD, OR, RR, HR. Auto-selects method by...

Parameters* required

comparisonsarray

Direct comparisons with effect sizes. Need at least 2 sharing a common comparator. Ask the user for: point estimate, 95% CI, outcome name, and effect measure (MD/OR/RR/HR) from each trial.

methodstring

auto (default): Bucher for simple paths, Frequentist NMA for 3+ edges. Or force a specific method.one of auto · bucher · frequentist_nma

targetobject

Optional: specific comparison to compute. Omit to compute all possible pairwise comparisons.

models.budget_impactEstimate the total budget impact of adopting a new intervention over 1-5 years. Follows ISPOR Budget Impact Analysis good practice guidelines (Mauskopf 2007, Sullivan 2014). Computes year-by-year net cost to payer, including market share uptake, treatment displacement, and pop...17 params

Estimate the total budget impact of adopting a new intervention over 1-5 years. Follows ISPOR Budget Impact Analysis good practice guidelines (Mauskopf 2007, Sullivan 2014). Computes year-by-year net cost to payer, including market share uptake, treatment displacement, and pop...

Parameters* required

admin_cost_annualnumber

Annual administration cost (applies to both arms). Default 0.

ae_cost_annualnumber

Annual adverse event cost for intervention. Default 0.

comparatorstring

Current standard of care

comparator_ae_cost_annualnumber

Annual adverse event cost for comparator. Default 0.

comparator_cost_annualnumber

Annual drug cost for comparator

displacementarray

Existing treatments displaced by intervention (share of patients switching, cost saved)

drug_cost_annualnumber

Annual drug acquisition cost for intervention

eligible_populationnumber

Number of eligible patients in Year 1

indicationstring

Disease or condition

interventionstring

New drug or treatment

market_shareobject

Expected market share of intervention by year (0-1). Missing years extrapolate from last defined.

monitoring_cost_annualnumber

Annual monitoring cost for intervention. Default 0.

output_formatstring

Use 'xlsx' for a structured Excel report with all inputs, year-by-year calculations, and audit trail in separate tabs. The workbook is a REPORT — editing cells does not re-run the model. Re-run by...one of text · json · docx · xlsx

perspectivestring

Payer perspective: 'nhs' (UK NHS), 'us_payer' (US commercial/Medicare), or 'societal' (broader costs incl. productivity). Determines currency and cost categories.one of nhs · us_payer · societal

population_growth_ratenumber

Annual population growth rate (e.g., 0.02 for 2%). Default 0.

projectstring

Project ID for persistence

time_horizon_yearsnumber

Budget horizon in years (1-10, default 5)

evidence.population_adjusted⚠️ EXPERIMENTAL / orientation-only. Approximate population-adjusted indirect comparison using summary-level statistics (mean, SD per covariate). True MAIC/STC per NICE DSU TSD 18 requires individual patient data (IPD) for one trial. This tool inflates the SE of a Bucher indire...7 params

⚠️ EXPERIMENTAL / orientation-only. Approximate population-adjusted indirect comparison using summary-level statistics (mean, SD per covariate). True MAIC/STC per NICE DSU TSD 18 requires individual patient data (IPD) for one trial. This tool inflates the SE of a Bucher indire...

Parameters* required

effect_modifiersarray

Names of covariates that are effect modifiers (must appear in both trials' covariates)

index_trialobject

Trial with data to be reweighted (the trial for which you want to adjust)

methodstring

auto (default): MAIC when >=2 modifiers and N>=50, else STCone of auto · maic · stc

outcome_namestring

Name of the outcome being compared (e.g., 'HbA1c change')

output_formatstring

one of text · json

projectstring

Project ID for persistence

target_trialobject

Trial whose population is the matching target

evidence.survivalFit parametric survival distributions (Exponential, Weibull, Log-logistic, Log-normal, Gompertz) to either patient-level event-time data (preferred — true right-censored MLE per Collett 2015 / NICE DSU TSD 14) OR Kaplan-Meier step-summary data (legacy approximation, used when...6 params

Fit parametric survival distributions (Exponential, Weibull, Log-logistic, Log-normal, Gompertz) to either patient-level event-time data (preferred — true right-censored MLE per Collett 2015 / NICE DSU TSD 14) OR Kaplan-Meier step-summary data (legacy approximation, used when...

Parameters* required

endpointstring

Endpoint name (e.g., 'OS', 'PFS', 'DFS'). Default: 'OS'.

event_dataarray

Patient-level event-time rows (PREFERRED — true MLE per NICE DSU TSD 14). Each row: { time, event } where event=1 for an observed event, event=0 for right-censoring. At least 5 rows required.

km_dataarray

Kaplan-Meier step-summary data points (LEGACY approximation; use event_data when patient-level data is available). At least 3 required. Extract from published KM curves or trial reports.

output_formatstring

one of text · json

projectstring

Project ID for persistence

time_unitstring

Time unit for KM data (default: months)one of months · years

literature.screenScreen literature search results using PICO criteria. Scores each abstract by relevance to the research question, classifies study design, and returns a ranked shortlist with inclusion/exclusion decisions and reasons. Pass the results array from a prior literature.search call...7 params

Screen literature search results using PICO criteria. Scores each abstract by relevance to the research question, classifies study design, and returns a ranked shortlist with inclusion/exclusion decisions and reasons. Pass the results array from a prior literature.search call...

Parameters* required

criteriaobject

PICO inclusion criteria

exclude_study_typesarray

Additional study types to exclude (e.g., ['case_report', 'narrative_review']). Editorials/commentaries are always excluded.

include_thresholdnumber

Relevance score threshold for inclusion (0-1, default 0.3). Lower = more inclusive.

min_yearnumber

Exclude studies published before this year

output_formatstring

one of text · json

projectstring

Project ID for persistence

resultsarray

Array of LiteratureResult objects from a prior literature.search call (use output_format='json')

evidence.risk_of_biasAssess risk of bias for a set of studies using the appropriate Cochrane instrument: RoB 2 (RCTs), ROBINS-I (observational studies), or AMSTAR-2 (systematic reviews/meta-analyses). Instrument is auto-detected from study_type or can be specified. Judgments are inferred from abst...4 params

Assess risk of bias for a set of studies using the appropriate Cochrane instrument: RoB 2 (RCTs), ROBINS-I (observational studies), or AMSTAR-2 (systematic reviews/meta-analyses). Instrument is auto-detected from study_type or can be specified. Judgments are inferred from abst...

Parameters* required

instrumentstring

Assessment instrument. auto (default) detects from study_type. rob2 for RCTs, robins_i for observational, amstar2 for systematic reviews.one of auto · rob2 · robins_i · amstar2

outcomesarray

Outcomes of interest for contextual domain assessment (optional)

output_formatstring

one of text · json

studiesarray

Array of study objects from screen_abstracts or literature_search (output_format='json')

utils.validate_linksValidate URLs by making HEAD requests and checking HTTP status codes. Returns categorization: working (200), browser_only (403 from bot-blocking sites that work in browsers), broken (404/410), or timeout/error. ALWAYS use this before presenting reference links to users — broke...2 params

Validate URLs by making HEAD requests and checking HTTP status codes. Returns categorization: working (200), browser_only (403 from bot-blocking sites that work in browsers), broken (404/410), or timeout/error. ALWAYS use this before presenting reference links to users — broke...

Parameters* required

timeout_msnumber

Timeout per URL in ms (default 10000, max 30000)

urlsarray

List of URLs to validate (max 50)

hta.utilityLook up EQ-5D value set characteristics (UK 3L, England 5L, new UK 5L 2026, NICE DSU mapping) or estimate the ICER/QALY impact of the new UK EQ-5D-5L value set for a given indication type. Cites Biz, Hernández Alava, Wailoo (2026) Value in Health. Use when user asks about NICE...5 params

Look up EQ-5D value set characteristics (UK 3L, England 5L, new UK 5L 2026, NICE DSU mapping) or estimate the ICER/QALY impact of the new UK EQ-5D-5L value set for a given indication type. Cites Biz, Hernández Alava, Wailoo (2026) Value in Health. Use when user asks about NICE...

Parameters* required

actionstring

'lookup' returns a single value set; 'compare' returns all four side-by-side; 'estimate_impact' returns ICER/QALY change estimates for an indication type.one of lookup · compare · estimate_impact

base_icernumber

Optional: current ICER to project forward under new UK 5L.

base_incremental_qalynumber

Optional: current incremental QALY gain to project forward under new UK 5L.

indication_typestring

Indication category (required for 'estimate_impact'). 'non_cancer_qol_only' = chronic QoL-only conditions (migraine, UC, atopic dermatitis, HS, plaque psoriasis) — sees the biggest ICER increase.one of cancer_life_extending · non_cancer_life_extending · non_cancer_qol_only

value_setstring

Value set id (required for 'lookup'). 'uk_5l_new' is the 2026 one under NICE consultation.one of uk_3l · england_5l · uk_5l_new · dsu_mapping

evidence.itcAssess the feasibility of an indirect treatment comparison (ITC) by walking through the three core assumptions (exchangeability, homogeneity, consistency) and recommending an appropriate method: direct comparison, Bucher, full NMA, anchored MAIC/STC, unanchored MAIC/STC, ML-NM...9 params

Assess the feasibility of an indirect treatment comparison (ITC) by walking through the three core assumptions (exchangeability, homogeneity, consistency) and recommending an appropriate method: direct comparison, Bucher, full NMA, anchored MAIC/STC, unanchored MAIC/STC, ML-NM...

Parameters* required

connected_networkboolean

True if there is a connected evidence network linking the treatments of interest via at least one common comparator.

effect_modifier_imbalancestring

Severity of imbalance in identified effect modifiers across trial populations. Default 'unknown'.one of none · minor · major · unknown

effect_modifiers_identifiedboolean

True if effect modifiers have been identified through clinical input or literature review. Default false.

h2h_availableboolean

True if at least one head-to-head RCT compares the treatments directly. Default false.

heterogeneity_i2_pctnumber

Optional: I² statistic (%) across studies of the same comparison. If absent, homogeneity is assessed qualitatively.

ipd_available_for_interventionboolean

True if individual patient data (IPD) are available from the sponsor's trial. Default false.

n_studies_per_comparisonnumber

Optional: minimum number of studies per pairwise comparison. Informs choice between Bucher (k=1) and NMA (k≥2).

outcome_typestring

Primary outcome type — guides estimator recommendations.one of binary · continuous · time_to_event

subgroup_data_availableboolean

True if subgroup data are available in comparator trials for adjustment. Default false.

examplesGet a pre-filled, copy-runnable JSON input for any of the heavy-schema tools (cost_effectiveness_model, budget_impact_model, survival_fitting, population_adjusted_comparison, evidence_indirect). Use when you want to demo a tool but don't want to invent inputs from scratch — th...1 params

Get a pre-filled, copy-runnable JSON input for any of the heavy-schema tools (cost_effectiveness_model, budget_impact_model, survival_fitting, population_adjusted_comparison, evidence_indirect). Use when you want to demo a tool but don't want to invent inputs from scratch — th...

Parameters* required

toolstring

Which tool to get an example for. Omit to list all available examples.one of

cost_effectiveness_model · budget_impact_model · survival_fitting · population_adjusted_comparison · evidence_indirect

workflow.maicRun the canonical MAIC discovery+screening pipeline in one call: ITC feasibility + parallel literature_search (broad + per-trial) + PICO screening + risk_of_bias + evidence_network. Stops short of running MAIC/Bucher itself (those require IPD or trial-level effect estimates)....10 params

Run the canonical MAIC discovery+screening pipeline in one call: ITC feasibility + parallel literature_search (broad + per-trial) + PICO screening + risk_of_bias + evidence_network. Stops short of running MAIC/Bucher itself (those require IPD or trial-level effect estimates)....

Parameters* required

comparatorstring

Comparator drug name.

effect_modifiersarray

Optional effect modifiers known from clinical input.

indicationstring

Disease/condition.

interventionstring

Drug/intervention name.

max_results_per_searchnumber

default: 50

outcome_typestring

one of binary · continuous · time_to_event

picoobject

Optional PICO criteria for screening (defaults derived).

runs_per_searchnumber

default: 2

trials_comparatorarray

Optional comparator-side trial names (e.g., INSPIRE, COMMAND).

trials_interventionarray

Optional trial names (e.g., QUASAR, ASTRO) to search in parallel.

pv.classifyClassify a planned study into its EMA pharmacovigilance regulatory category (PASS imposed/voluntary, PAES, RMP Annex 4, DUS, active surveillance registry, pregnancy registry, spontaneous reporting, ICH E2E plan). Returns the matching GVP module + ENCePP study-category label (n...10 params

Classify a planned study into its EMA pharmacovigilance regulatory category (PASS imposed/voluntary, PAES, RMP Annex 4, DUS, active surveillance registry, pregnancy registry, spontaneous reporting, ICH E2E plan). Returns the matching GVP module + ENCePP study-category label (n...

Parameters* required

drugstring

Drug name.

imposed_by_authorityboolean

default: false

indicationstring

Disease/condition.

jurisdictionsarray

multi_countryboolean

default: false

population_includes_paediatricboolean

default: false

population_includes_pregnantboolean

default: false

primary_objectivestring

one of safety · efficacy · effectiveness · drug_utilization · natural_history · risk_minimisation_evaluation

regulatory_contextstring

one of pre_authorisation · post_authorisation · conditional_approval · accelerated_approval · rmp_commitment

study_designstring

one of rct · single_arm · prospective_cohort · retrospective_cohort · case_control · registry

jca.pico_scopeProduce the canonical EU Joint Clinical Assessment (JCA) PICO matrix for a drug-indication pair. Returns a consolidated PICO list (per JCA process under Reg. 2021/2282) plus country-specific comparator universes, outcome instrument preferences, population subgroup focus, and a...10 params

Produce the canonical EU Joint Clinical Assessment (JCA) PICO matrix for a drug-indication pair. Returns a consolidated PICO list (per JCA process under Reg. 2021/2282) plus country-specific comparator universes, outcome instrument preferences, population subgroup focus, and a...

Parameters* required

biomarker_statusstring

Optional biomarker status (e.g., 'EGFR T790M positive', 'PD-L1 TPS ≥50%').

drugstring

Drug name.

drug_classstring

one of monoclonal_antibody · small_molecule · atmp_cell · atmp_gene · atmp_tissue · biosimilar

force_proceed_out_of_scopeboolean

Override the JCA scope eligibility check. Default false. Set true to produce a JCA-style matrix anyway when the indication is not yet in JCA scope (e.g., for protocol-design or anticipatory market-...default: false

indicationstring

Disease/condition.

is_orphanboolean

Optional. Orphan-designated medicinal product. Affects JCA scope eligibility (orphans enter scope from 13 January 2028 vs 13 January 2030 for general medicinal products).

jurisdictionsarray

line_of_therapystring

one of first_line · second_line · third_line_plus · anydefault: any

mechanism_of_actionstring

regulatory_contextstring

one of pre_authorisation · post_authorisation · conditional_approvaldefault: post_authorisation

pv.signal_workflowCompute disproportionality statistics (PRR, ROR, IC/BCPNN, MGPS/EBGM) on user-supplied drug-AE case counts and decide a signal verdict per EMA GVP Module IX rev 2. Returns the verdict (no/strengthening/confirmed/previously known/refuted), workflow recommendations, and canonica...9 params

Compute disproportionality statistics (PRR, ROR, IC/BCPNN, MGPS/EBGM) on user-supplied drug-AE case counts and decide a signal verdict per EMA GVP Module IX rev 2. Returns the verdict (no/strengthening/confirmed/previously known/refuted), workflow recommendations, and canonica...

Parameters* required

case_countsobject

data_sourcestring

one of eudravigilance · faers · vigibase_who · national_db · spontaneous_internaldefault: eudravigilance

drugstring

indicationstring

outcome_seriousboolean

default: false

pregnancy_exposureboolean

default: false

prior_known_signalsarray

reporting_period_monthsnumber

default: 12

rmp_has_pregnancy_concernboolean

default: false

hta.workflowEnd-to-end HTA submission orchestrator. One call runs literature_search (with PRISMA-style stability via runs=N) → screen_abstracts (PICO filter) → risk_of_bias (auto RoB 2/ROBINS-I/AMSTAR-2) → cost_effectiveness_model (Markov + 1k PSA, defaults from indication) → hta_dossier...16 params

End-to-end HTA submission orchestrator. One call runs literature_search (with PRISMA-style stability via runs=N) → screen_abstracts (PICO filter) → risk_of_bias (auto RoB 2/ROBINS-I/AMSTAR-2) → cost_effectiveness_model (Markov + 1k PSA, defaults from indication) → hta_dossier...

Parameters* required

auto_check_regulatoryboolean

When true (default), Phase 3.6 fans out regulatory.status_check across comparators from pico.comparator and unmet_need_inputs.treatment_landscape.current_soc. Results piped into hta_dossier as regu...default: true

ce_inputsobject

Optional cost-effectiveness model inputs. Sensible defaults applied when omitted (efficacy_delta=0.25; drug_cost_annual=1000; SoC=0).

drugstring

Drug or intervention name.

drug_classstring

one of monoclonal_antibody · small_molecule · atmp_cell · atmp_gene · atmp_tissue · biosimilardefault: small_molecule

hta_bodystring

Target HTA body for the dossier draft.one of nice · ema · fda · iqwig · has · jcadefault: nice

indicationstring

Disease or condition (free text).

is_orphanboolean

Orphan-designated medicinal product. Affects JCA scope eligibility (orphans enter JCA scope 2028 vs 2030 for general medicinal products).default: false

jurisdictionsarray

literature_runsnumber

Number of dedup-stability passes for the literature_search phase. 3 is the project default for HTA-grade reproducibility.default: 3

max_literature_resultsnumber

default: 30

perspectivestring

Economic perspective for the cost-effectiveness model phase.one of nhs · us_payer · societaldefault: nhs

picoobject

Optional PICO criteria for the screening phase (defaults derived from drug + indication).

skip_ce_modelboolean

Skip the cost-effectiveness model phase (e.g., for clinical-only dossiers).default: false

sourcesarray

submission_typestring

one of sta · mta · early_access · initial · renewal · variationdefault: sta

unmet_need_inputsobject

Optional structured inputs for Phase 3.5 (evidence.unmet_need). Only consumed when hta_body='gvd'. When supplied, the orchestrator runs evidence.unmet_need and pipes the resulting unmet_need_summar...

irb.reviewClassify a planned study under 45 CFR 46 (US Common Rule) + EU CTR 536/2014 to produce an IRB / Ethics Committee submission scaffold. Returns: review tier (exempt §46.104 cat 1-8 / expedited §46.110 cat 1-7 / full-board §46.108), EU CTR review path with timeline, vulnerable-po...24 params

Classify a planned study under 45 CFR 46 (US Common Rule) + EU CTR 536/2014 to produce an IRB / Ethics Committee submission scaffold. Returns: review tier (exempt §46.104 cat 1-8 / expedited §46.110 cat 1-7 / full-board §46.108), EU CTR review path with timeline, vulnerable-po...

Parameters* required

benign_behaviouralboolean

Set true for benign behavioural interventions in adults (45 CFR 46.104(d)(3)).

blood_draw_within_limitsboolean

Set true for blood collection within OHRP volume limits (45 CFR 46.110 cat 2).

broad_consent_obtainedboolean

Set true when broad consent has been obtained for secondary research / specimen storage (45 CFR 46.104(d)(7-8)).

data_handlingstring

one of fully_identifiable · pseudonymized · anonymized_safe_harbor · anonymized_expert_determination · aggregate_only

exempt_category_hintstring

Hint: flag this as 45 CFR 46.104(d)(1) educational practices research.one of educational

expedited_category_claimarray

Expedited review categories per 45 CFR 46.110 (1-7) the investigator believes apply. Tool will validate; if it disagrees, both are surfaced as advisory_warnings.

federal_demonstrationboolean

Set true for federally supported research / demonstration project (45 CFR 46.104(d)(5)).

funding_sourcestring

one of industry · nih · other_government · foundation · academic · none

indicationstring

interventionstring

jurisdictionsarray

marketed_drugboolean

Set true when the study uses a marketed drug per labeling (drives expedited cat 1, post-marketing PSUR framework).

multi_siteboolean

default: false

noninvasive_collectionboolean

Set true for prospective biospecimen collection by noninvasive means (45 CFR 46.110 cat 3).

noninvasive_procedureboolean

Set true for noninvasive data collection (ECG, EEG, blood pressure, ultrasound) (45 CFR 46.110 cat 4).

population_includes_decisionally_impairedboolean

default: false

population_includes_pediatricboolean

default: false

population_includes_pregnantboolean

default: false

population_includes_prisonersboolean

default: false

pv_classificationobject

Optional structured output from pv_classify. Only primary_category is read; PASS_imposed triggers CTR Annex III SAE timelines.

+4 more parameters. See the server's own documentation for the full schema.

icf.readability_checkScore the readability of an Informed Consent Form (ICF) text. Returns Flesch-Kincaid Grade Level, Flesch Reading Ease, Gunning Fog Index, SMOG Grade, plus per-sentence breakdown identifying the worst offenders, medical-jargon detection with plain-language alternatives, and a p...3 params

Score the readability of an Informed Consent Form (ICF) text. Returns Flesch-Kincaid Grade Level, Flesch Reading Ease, Gunning Fog Index, SMOG Grade, plus per-sentence breakdown identifying the worst offenders, medical-jargon detection with plain-language alternatives, and a p...

Parameters* required

icf_textstring

The ICF body text. Plain text or markdown both work.

jargon_checkboolean

Whether to run the medical-jargon dictionary lookup. Default true.default: true

target_grade_levelinteger

Target US grade level for FKGL pass verdict. FDA/NIH typically 8; some IRBs use 6 (stricter).default: 8

evidence.clinical_scaleScore neurology & cognitive outcome scales (UMSARS/UPDRS/MDS-UPDRS/ADAS-Cog/MoCA/MMSE). Returns total + subscale scores, MCID-based responder classification, and trajectory comparison vs NNIPPS/PPMI/ADNI reference cohorts. Integrates with jca_pico_scope for MSA (neurology_msa,...5 params

Score neurology & cognitive outcome scales (UMSARS/UPDRS/MDS-UPDRS/ADAS-Cog/MoCA/MMSE). Returns total + subscale scores, MCID-based responder classification, and trajectory comparison vs NNIPPS/PPMI/ADNI reference cohorts. Integrates with jca_pico_scope for MSA (neurology_msa,...

Parameters* required

baseline_itemsarray

Optional: baseline scores for change-from-baseline and responder analysis.

compare_cohortstring

Natural-history reference cohort for trajectory comparison. nnipps=MSA, ppmi=PD, adni=AD.one of nnipps · ppmi · adni · none

itemsarray

Per-item scores. Supply all items for complete scoring, or a subset for partial scoring with a note.

scalestring

time_point_monthsnumber

Time point in months from baseline (used for trajectory comparison).

evidence.unmet_needGenerate a structured unmet need section for HTA dossiers (NICE STA, EMA, FDA, IQWiG, HAS, JCA, GVD, AMCP). Consume-only: first retrieve evidence with literature_search, then pass only cited facts across 4 HEOR dimensions — disease burden, treatment landscape, QoL impact, econ...9 params

Generate a structured unmet need section for HTA dossiers (NICE STA, EMA, FDA, IQWiG, HAS, JCA, GVD, AMCP). Consume-only: first retrieve evidence with literature_search, then pass only cited facts across 4 HEOR dimensions — disease burden, treatment landscape, QoL impact, econ...

Parameters* required

auto_check_regulatoryboolean

When true (default), automatically fans out regulatory.status_check for each drug in treatment_landscape.current_soc × inferred regions. Injects verbatim label quotes inline with auto-numbered cita...default: true

disease_burdenobject

Epidemiology data for the indication

drugstring

Drug or intervention name

economic_burdenobject

Direct and indirect economic burden of the disease

indicationstring

Disease/condition being treated

jurisdictionsarray

Target market(s) for this unmet need assessment

literature_evidencearray

Optional: pass literature_search results here to include as supporting evidence

qol_impactobject

Patient-reported and health-related quality of life impact

treatment_landscapeobject

Current standard of care and its limitations. Use only evidence retrieved by literature_search or other audited sources. Regulatory/approval claims require current label/regulatory citation support...

regulatory.status_checkLook up current regulatory approval status for a drug from primary sources (OpenFDA for US, EMA EPI for EU). Returns approved indications, label text verbatim, age/weight/sex constraints, black-box warnings, REMS status, contraindications, source URLs, and fetch timestamp. Ref...5 params

Look up current regulatory approval status for a drug from primary sources (OpenFDA for US, EMA EPI for EU). Returns approved indications, label text verbatim, age/weight/sex constraints, black-box warnings, REMS status, contraindications, source URLs, and fetch timestamp. Ref...

Parameters* required

drugstring

Drug name: INN (fremanezumab), INN+suffix (fremanezumab-vfrm), or brand (Ajovy, case-insensitive).

force_refreshboolean

Bypass 24h cache and re-fetch from primary source. Use for same-day label changes.default: false

include_label_historyboolean

Reserved for v1.7.2 — ignored in v1.7.0.default: false

indicationstring

Optional: narrow results to indications containing this text (e.g., 'pediatric', 'migraine').

regionstring

Regulatory region. 'uk' deferred to v1.7.1 (no public eMC API). 'global' queries US.one of us · eu · uk · global

governance.self_checkScore an AI-assisted HTA/HEOR workflow against 6 governance dimensions (transparency, citation validation, human-in-the-loop, PHI/data handling, bias & equity, auditability), each traced to the verified ELEVATE-GenAI reporting domains (ISPOR Working Group on Generative AI, Val...6 params

Score an AI-assisted HTA/HEOR workflow against 6 governance dimensions (transparency, citation validation, human-in-the-loop, PHI/data handling, bias & equity, auditability), each traced to the verified ELEVATE-GenAI reporting domains (ISPOR Working Group on Generative AI, Val...

Parameters* required

ai_disclosure_levelstring

AI assistance disclosure level appended to the output. "off" = no disclosure (analyst scratch mode); "standard" = default visible block (model, tools called, sources, date, human-review reminder);...one of off · standard · submission

audit_recordobject

A prior HEORAgent AuditRecord (audit_record mode). Auto-derives transparency/citation/auditability.

contextobject

modestring

'describe' = score a workflow_description + probes; 'audit_record' = auto-derive from a HEORAgent AuditRecord.one of describe · audit_recorddefault: describe

probesobject

One probe per dimension. Each is {answer: 'yes'|'no'|'partial'|null, detail?}. Omit or null → scored 'insufficient' (never a pass).

workflow_descriptionstring

Free-text description of the AI-assisted workflow: what the AI does and where its output goes.

data.claims_queryQuery real-world claims and survey data across 14 datasets spanning the US and Latin America. US datasets: meps (expenditure survey, 2017-2023, costs in USD), namcs (physician office visits 2018-2022), nhamcs_ed (ED visits 2011-2022), ny_sparcs (NY inpatient 2017-2024, costs i...11 params

Query real-world claims and survey data across 14 datasets spanning the US and Latin America. US datasets: meps (expenditure survey, 2017-2023, costs in USD), namcs (physician office visits 2018-2022), nhamcs_ed (ED visits 2011-2022), ny_sparcs (NY inpatient 2017-2024, costs i...

Parameters* required

age_maxinteger

age_mininteger

aggregationstring

prevalence or count: record counts + weighted estimates by year — USE THIS for population sizing and budget impact. drug_utilization: top drugs by frequency. demographics: age/sex breakdown. comorb...one of prevalence · count · drug_utilization · demographics · comorbidities · cost

datasetsarray

drug_namesarray

Substring match in drug list. E.g. ['metformin'] or ['empagliflozin', 'dapagliflozin'].

icd10_prefixesarray

ICD-10 prefixes: ['E11'] = T2D, ['I21'] = AMI, ['C50'] = breast cancer, ['J45'] = asthma.

regionsarray

Region/state filter. Brazil datasus UF codes: ['SP'] = São Paulo, ['SP','RJ','MG'] = top 3 states. US NAMCS/MEPS census regions: ['Northeast','South','West','Midwest']. Omit for all regions.

sexstring

one of male · female · alldefault: all

top_ninteger

default: 20

year_frominteger

year_tointeger

data.query_agentValidated epidemiology agent. Use this INSTEAD of data.claims_query when you need population-level estimates for budget impact models or population sizing. Automatically resolves clinical indications to ICD-10 codes, selects the right dataset by country, runs the query, valida...10 params

Validated epidemiology agent. Use this INSTEAD of data.claims_query when you need population-level estimates for budget impact models or population sizing. Automatically resolves clinical indications to ICD-10 codes, selects the right dataset by country, runs the query, valida...

Parameters* required

additional_icd_prefixesarray

Override or supplement auto-resolved ICD-10 prefixes. Use when the indication isn't in the built-in map.

age_maxinteger

age_mininteger

country_codesarray

ISO-2 country codes: ['BR'], ['US'], ['MX'], ['EC'], ['UY'], ['CO'], ['AR'].

indicationstring

Clinical indication in plain English: 'type 2 diabetes inpatient', 'heart failure', 'COPD', 'breast cancer'. Maps to ICD-10 automatically.

purposestring

Drives how the recommended_estimate is framed in the output.one of population_sizing · budget_impact · epidemiologydefault: population_sizing

regionsarray

Optional region filter. Brazil UF codes: ['SP','RJ','MG']. US census: ['Northeast','South'].

sexstring

one of male · female · alldefault: all

year_frominteger

year_tointeger

Readme

HEORAgent MCP Server

AI-powered Health Economics and Outcomes Research (HEOR) agent as a Model Context Protocol server.

View the full README on GitHub

Details

Repository: github.com/neptun2000/heor-agent-mcp
Categories: AI & LLM Tools, Search & Web Crawling
Package: heor-agent-mcp
Transport: STDIO
Registry: MCP registry, active

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