HEORAgent MCP Server

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

Automates literature review across 42 data sources, risk of bias assessment (RoB 2 / ROBINS-I / AMSTAR-2), state-of-the-art cost-effectiveness modelling, HTA dossier preparation for NICE / EMA / FDA / IQWiG / HAS / EU JCA, and a persistent project knowledge base — all callable as MCP tools from Claude.ai, Claude Code, and any MCP-compatible host.

Built for pharmaceutical, biotech, CRO, and medical affairs teams who need rigorous, auditable HEOR workflows without building infrastructure from scratch.

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Quick Start

Claude Code

claude mcp add heor-agent -- npx heor-agent-mcp

Then restart Claude Code.

Claude Desktop / claude.ai

Add to your MCP configuration:

{
  "mcpServers": {
    "heor-agent": {
      "command": "npx",
      "args": ["heor-agent-mcp"]
    }
  }
}

Verify

> Run a literature search for semaglutide cost-effectiveness in T2D using PubMed and NICE TAs

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Tools

Tool	Purpose
literature_search	Search 42 data sources with a full PRISMA-style audit trail
screen_abstracts	PICO-based relevance scoring and study design classification
risk_of_bias	Cochrane RoB 2 / ROBINS-I / AMSTAR-2 with GRADE RoB domain summary
cost_effectiveness_model	Markov / PartSA / decision-tree CEA with PSA, OWSA, CEAC, EVPI
hta_dossier_prep	Draft submissions for NICE, EMA, FDA, IQWiG, HAS, and EU JCA — GRADE table uses structured RoB when rob_results passed
project_create	Initialize a persistent project workspace
knowledge_search	Full-text search across a project's raw/ and wiki/ trees
knowledge_read	Read any file from a project's knowledge base
knowledge_write	Write compiled evidence to the project wiki (Obsidian-compatible)

literature_search

Searches across 42 sources in parallel. Every call returns a source selection table showing which of the 42 sources were used and why — essential for HTA audit trails.

Example call:

{
  "query": "semaglutide cardiovascular outcomes type 2 diabetes",
  "sources": ["pubmed", "clinicaltrials", "nice_ta", "cadth_reviews", "icer_reports"],
  "max_results": 20,
  "output_format": "text"
}

cost_effectiveness_model

Multi-state Markov model (default) or Partitioned Survival Analysis (oncology), following ISPOR good practice and NICE reference case (3.5% discount rate, half-cycle correction). Includes:

• PSA — 1,000–10,000 Monte Carlo iterations, probability cost-effective at WTP thresholds
• OWSA — one-way sensitivity analysis with tornado summary
• CEAC — cost-effectiveness acceptability curve
• EVPI — expected value of perfect information
• WTP assessment — verdict against NHS (£25–35K/QALY, updated April 2026), US payer ($100–150K), societal thresholds

Example call:

{
  "intervention": "Semaglutide 1mg SC weekly",
  "comparator": "Sitagliptin 100mg daily",
  "indication": "Type 2 Diabetes Mellitus",
  "time_horizon": "lifetime",
  "perspective": "nhs",
  "model_type": "markov",
  "clinical_inputs": { "efficacy_delta": 0.5, "mortality_reduction": 0.15 },
  "cost_inputs": { "drug_cost_annual": 3200, "comparator_cost_annual": 480 },
  "utility_inputs": { "qaly_on_treatment": 0.82, "qaly_comparator": 0.76 },
  "run_psa": true,
  "output_format": "docx"
}

hta_dossier_prep

Drafts submission-ready sections for six HTA frameworks with gap analysis:

Body	Country	Submission types
NICE	UK	STA, MTA, early_access
EMA	EU	STA, MTA
FDA	US	STA, MTA
IQWiG	Germany	STA, MTA
HAS	France	STA, MTA
JCA	EU (Reg. 2021/2282)	initial, renewal, variation (with PICOs)

Accepts piped output from literature_search and cost_effectiveness_model.

risk_of_bias

Assesses risk of bias using the appropriate Cochrane instrument, auto-detected from study_type:

Study type	Instrument
RCT	RoB 2 (5 domains: randomization, deviations, missing data, measurement, reporting)
Observational	ROBINS-I (7 domains: confounding, selection, classification, deviations, missing data, measurement, reporting)
Systematic review	AMSTAR-2 (16 items, critical vs non-critical)

Returns a rob_results object you can pass directly to hta_dossier_prep — this replaces the heuristic RoB estimate in the GRADE table with structured domain judgments.

Example call:

{
  "studies": [{ "id": "pmid_1", "study_type": "RCT", "title": "...", "abstract": "..." }],
  "output_format": "json"
}

Pipeline:

literature_search → screen_abstracts → risk_of_bias → hta_dossier_prep

Knowledge base tools

Projects live at ~/.heor-agent/projects/{project-id}/ with:

• raw/literature/ — auto-populated literature search results
• raw/models/ — auto-populated model runs
• raw/dossiers/ — auto-populated dossier drafts
• reports/ — generated DOCX files
• wiki/ — manually curated, Obsidian-compatible markdown with [[wikilinks]]

Pass project: "project-id" to any tool and results are saved automatically.

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Examples

Copy-paste prompts to try in Claude Code, Claude Desktop, or the web UI.

Single-tool examples

Literature search

Search the literature for tirzepatide cardiovascular outcomes in type 2 diabetes. Use PubMed, ClinicalTrials.gov, and NICE TAs.

Survival curve fitting

Fit survival curves to this OS data from KEYNOTE-189: time 0 survival 1.0, time 6 survival 0.88, time 12 survival 0.72, time 18 survival 0.60, time 24 survival 0.51, time 36 survival 0.38. Use months.

Budget impact

Estimate the 5-year NHS budget impact of semaglutide for obesity. 200,000 eligible patients, drug cost £1,200/year, comparator (orlistat) £250/year, uptake 15% year 1 to 40% year 5.

Cost-effectiveness model

Build a CE model for semaglutide vs sitagliptin in T2D, NHS perspective, lifetime horizon, with PSA.

Indirect comparison (Bucher)

I have two trials: SUSTAIN-1 showed semaglutide vs placebo HR 0.74 (0.58-0.95) for HbA1c, and AWARD-5 showed dulaglutide vs placebo HR 0.78 (0.65-0.93). Run a Bucher indirect comparison between semaglutide and dulaglutide.

MAIC (population-adjusted comparison)

Run a MAIC between SUSTAIN-7 (N=300, semaglutide vs placebo, HR 0.74, CI 0.58-0.95, age 56±10, BMI 33±5) and AWARD-11 (N=600, dulaglutide vs placebo, HR 0.78, CI 0.65-0.93, age 58±9, BMI 35±6). Adjust for age and BMI.

Multi-tool workflows

Abstract screening workflow

Search PubMed for pembrolizumab in NSCLC, then screen the results with population adults with NSCLC, intervention pembrolizumab, comparator chemotherapy, outcomes overall survival and PFS.

Evidence network + NMA feasibility

Search for GLP-1 receptor agonists in T2D using PubMed, build an evidence network from the results, and assess NMA feasibility.

CE model with scenarios

Build a CE model for dapagliflozin vs placebo in heart failure, NHS perspective, lifetime horizon, with PSA. Add scenarios: "20% price reduction" with drug cost 400, "10-year horizon" with time_horizon 10yr.

End-to-end HTA workflow

Full dossier preparation

Create a project for semaglutide in obesity targeting NICE and ICER. Search literature for evidence, screen the results for adults with obesity comparing semaglutide to placebo for weight loss outcomes, assess risk of bias on the screened studies, then draft a NICE STA dossier using the screened results and rob_results.

This single prompt exercises: project_create → literature_search → screen_abstracts → risk_of_bias → hta_dossier_prep (GRADE RoB from structured assessment).

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Data Sources

42 sources across 9 categories. Every literature_search call includes a source selection table showing used/not-used status and reason for each.

• PubMed — 35M+ biomedical citations (NCBI E-utilities)
• ClinicalTrials.gov — NIH/NLM trial registry (CT.gov v2 API)
• bioRxiv / medRxiv — Life sciences and medical preprints
• ChEMBL — Drug bioactivity, mechanisms, ADMET (EMBL-EBI)
• Wiley Online Library — Pharmacoeconomics, Health Economics, Journal of Medical Economics, Value in Health (CrossRef, ~77% abstract coverage, no key required)

• WHO GHO — WHO Global Health Observatory
• World Bank — Demographics, macroeconomics, health expenditure
• OECD Health — OECD health statistics (expenditure, workforce, outcomes)
• IHME GBD — Global Burden of Disease (DALYs, prevalence across 204 countries)
• All of Us — NIH precision medicine cohort

• FDA Orange Book — Drug approvals and therapeutic equivalence
• FDA Purple Book — Licensed biologics and biosimilars

• NICE TAs (UK) · CADTH (Canada) · ICER (US) · PBAC (Australia)
• G-BA AMNOG (Germany) · IQWiG (Germany) · HAS (France)
• AIFA (Italy) · TLV (Sweden) · INESSS (Quebec, Canada)

• CMS NADAC (US drug acquisition costs)
• PSSRU (UK unit costs) · NHS National Cost Collection · BNF (UK drug pricing)
• PBS Schedule (Australia)

• DATASUS · CONITEC · ANVISA (Brazil)
• PAHO (Pan American regional) · IETS (Colombia) · FONASA (Chile)

• HITAP (Thailand)

Source	Env variable
Embase	ELSEVIER_API_KEY
ScienceDirect	ELSEVIER_API_KEY
Cochrane Library	COCHRANE_API_KEY
Citeline	CITELINE_API_KEY
Pharmapendium	PHARMAPENDIUM_API_KEY
Cortellis	CORTELLIS_API_KEY
Google Scholar	SERPAPI_KEY

• ISPOR — HEOR methodology and conference abstracts

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Output Formats

All tools support output_format:

• text (default) — Markdown with formatted tables and headings
• json — Structured objects for downstream tools
• docx — Microsoft Word document, saved to disk, path returned in response

DOCX files are saved to ~/.heor-agent/projects/{project}/reports/ (when a project is set) or ~/.heor-agent/reports/ (global). The tool response contains the absolute path — ready to attach to submissions or share with stakeholders.

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Audit Trail

Every tool call returns a full audit record:

• Source selection table — all 42 sources with used/not-used and reason
• Sources queried — queries sent, response counts, status, latency
• Inclusions / exclusions — counts with reasons
• Methodology — PRISMA-style for literature, ISPOR/NICE for economics
• Assumptions — every assumption logged with justification
• Warnings — data quality flags, missing API keys, failed sources

Suitable for inclusion in HTA submission appendices.

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Configuration

# Optional — enterprise data sources
ELSEVIER_API_KEY=...        # Embase + ScienceDirect
COCHRANE_API_KEY=...        # Cochrane Library
CITELINE_API_KEY=...        # Citeline
PHARMAPENDIUM_API_KEY=...   # Pharmapendium
CORTELLIS_API_KEY=...       # Cortellis
SERPAPI_KEY=...             # Google Scholar

# Optional — knowledge base location
HEOR_KB_ROOT=~/.heor-agent  # Default

# Optional — localhost proxy for enterprise APIs behind corporate VPN
HEOR_PROXY_URL=http://localhost:8787

# Optional — hosted tier (future)
HEOR_API_KEY=...

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Web UI

A companion chat interface is available at:

https://web-michael-ns-projects.vercel.app

• Chat with Claude Opus 4.6 + all 7 HEOR tools
• BYOK (Bring Your Own Key) — paste your Anthropic API key in the settings; it stays in your browser's localStorage and is never stored on our servers
• Markdown rendering with styled tables, tool call cards with live progress timers
• Example prompts for common HEOR workflows

The web UI calls the hosted MCP server on Railway for tool execution. No setup required — just add your API key and start querying.

Self-hosting the web UI

cd web
npm install
echo "ANTHROPIC_API_KEY=sk-ant-..." > .env.local  # optional server-side fallback
npm run dev -- -p 3456

Set MCP_SERVER_URL to point to your own MCP server instance (default: the public Railway deployment).

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HTTP Transport

The server supports both stdio (default, for local MCP clients) and Streamable HTTP (for hosted deployment).

# Stdio mode (default — for Claude Code, Claude Desktop)
npx heor-agent-mcp

# HTTP mode — for hosted deployment, Smithery, web UI backend
npx heor-agent-mcp --http                    # port 8787
MCP_HTTP_PORT=3000 npx heor-agent-mcp        # custom port

HTTP endpoints:

• POST/GET/DELETE /mcp — MCP Streamable HTTP protocol
• GET /health — health check
• GET /.well-known/mcp/server-card.json — Smithery discovery

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Development

git clone https://github.com/neptun2000/heor-agent-mcp
cd heor-agent-mcp
npm install
npm test          # 244 tests across 66 suites
npm run build     # Compile TypeScript to dist/
npm run dev       # Run with tsx (no build step)

Requires: Node.js ≥ 20.

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Architecture

┌────────────────────────────────────────────┐
│  MCP Host (Claude.ai / Claude Code / etc.) │
└────────────────┬───────────────────────────┘
                 │ stdio
┌────────────────▼──────────────────────────┐
│  heor-agent-mcp server                    │
│  ┌──────────────────────────────────────┐ │
│  │ 7 MCP tools (Zod-validated)          │ │
│  ├──────────────────────────────────────┤ │
│  │ DirectProvider (default)             │ │
│  │   ├─ 42 source fetchers              │ │
│  │   ├─ Audit builder + PRISMA trail    │ │
│  │   ├─ Markov / PartSA economic models │ │
│  │   ├─ Markdown + DOCX formatters      │ │
│  │   └─ Knowledge base (YAML + MD)      │ │
│  └──────────────────────────────────────┘ │
└───────────────────────────────────────────┘
                 │
    ┌────────────┴─────────────┐
    ▼                          ▼
┌────────────┐         ┌──────────────────┐
│ ~/.heor-   │         │ External APIs    │
│ agent/     │         │ (PubMed, NICE,   │
│ projects/  │         │  ICER, CADTH, …) │
└────────────┘         └──────────────────┘

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License

MIT — see LICENSE.

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Disclaimer

All outputs are preliminary and for research orientation only. Results require validation by a qualified health economist before use in any HTA submission, payer negotiation, regulatory filing, or clinical decision. This tool does not replace professional HEOR expertise.

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Distribution

Channel	How to use	Who pays
npm	npx heor-agent-mcp	User's Claude subscription
Smithery	smithery.ai/servers/neptun2000-70zu/heor-agent-mcp	User's Claude subscription
Web UI	web-michael-ns-projects.vercel.app	User's own Anthropic API key (BYOK)
Hosted MCP	https://heor-agent-mcp-production.up.railway.app	Free (tool execution only)

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Links

• npm: https://www.npmjs.com/package/heor-agent-mcp
• GitHub: https://github.com/neptun2000/heor-agent-mcp
• Smithery: https://smithery.ai/servers/neptun2000-70zu/heor-agent-mcp
• Web UI: https://web-michael-ns-projects.vercel.app
• Issues: https://github.com/neptun2000/heor-agent-mcp/issues