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neptun2000/heor-agent-mcp

neptun2000/heor-agent-mcp

/ ROBINS-I / AMSTAR-2), EQ-5D value set impact estimation, 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.
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add heor-agent-mcp -- npx -y heor-agent-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
9 ★ · neptun2000/heor-agent-mcp · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 9 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 neptun2000/heor-agent-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

HEORAgent MCP Server

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**AI-powered Health Economics and Outcomes Research (HEOR) agent as a Model Context Protocol server.**
> **Try it now →** HEORAgent on ChatGPT (ChatGPT Plus / Team)
> · Web UI (Claude, BYOK)
> · npx heor-agent-mcp for Claude Desktop / Claude Code
Automates literature review across 44 data sources, risk of bias assessment (RoB 2 / ROBINS-I / AMSTAR-2), EQ-5D value set impact estimation, 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.
---
First 60 seconds
Verify your install works **before** wiring it into Claude / Cursor / Continue. Open two terminal tabs:
**Tab 1 — start the server in HTTP mode:**
You should see:
**Tab 2 — confirm it responds:**
Expected output:
✅ If you see the JSON above, the npm package works on your machine. Any further issues are in your MCP client config (Claude Desktop / Cursor / Continue), not the server.
❌ If you see command not found, run node --version — you need Node ≥20. If you see a different error, file a quick issue at https://github.com/neptun2000/heor-agent-mcp/issues with the output.
Now stop Tab 1 (Ctrl+C) and pick your client below — you don't need the HTTP mode for the actual integration; Claude / Cursor / Continue all use stdio.
---
Quick Start (per client)
Pick your MCP host:
Claude Code
Then restart Claude Code.
Claude Desktop / claude.ai Desktop
Edit your MCP config file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS) and add:
Then restart Claude Desktop.
Cursor / Continue / Cline
Same config shape as Claude Desktop above; the file path differs by client:
- **Cursor:** Settings → MCP → Add new MCP server
- **Continue:** ~/.continue/config.json under the mcpServers key
- **Cline:** Settings → MCP Servers → Edit MCP Settings
Hosted (no install)
- **ChatGPT (Plus / Team):** HEORAgent on ChatGPT — type /heor to use it; works on any conversation.
- **Web UI (Claude, BYOK):** web-michael-ns-projects.vercel.app — bring your Anthropic API key; runs the full v1.6.3 toolset.
---
Your first prompt
Once your MCP host is configured, paste any of these to verify end-to-end:
The first prompt exercises literature_search + validate_links (free, no API keys needed). The second exercises irb_review (pure decision tree, instant). The third exercises jca_pico_scope → hta_dossier pipeline.
---
What's new
See CHANGELOG.md for full version history. Current: **v1.23.0** (45 tools, 44 data sources).
v1.17.0–v1.23.0 — Living Evidence Intelligence (review → reimbursement)
A connected RWE + cross-deliverable layer (see docs/FEATURES.md for the full table):
- **RWE & real-world safety:** rwe.method_select (study-design selection), pv.comparative_safety (class-level FAERS-style AE ranking), evidence.triangulation (per-outcome RCT↔RWE concordance).
- **Governed social listening:** rwe.social_listening_protocol + pv.social_listening_triage (GVP Module VI ICSR triage — no scraping).
- **One source of truth:** evidence.claim_registry (author/auto-import a figure once), evidence.consistency_check (detect drift across dossier/publication/payer), publication.draft (reuse claims; CONSORT/STROBE/PRISMA/CHEERS + GPP2022/ICMJE).
- **Living orchestration:** evidence.gap_analysis (iEGP), workflow.living_evidence (SLR → living KB → JCA/HTA runbook), hta.living_gvd (regenerate only the GVD sections whose figures changed).
v1.13.0 — AI Transparency Disclosure (ISPOR ELEVATE-GenAI aligned)
16 tools now accept an ai_disclosure_level parameter:
| Value | Behaviour |
|-------|-----------|
| "off" | No disclosure block appended |
| "standard" | Model ID · tools called · data sources · date · human-review reminder |
| "submission" | Standard block + ISPOR ELEVATE-GenAI full citation |
**Default by tool tier**: HTA/regulatory tools (hta_dossier, hta_workflow, jca_pico_scope, pv_classify, etc.) default to "submission"; analysis tools (risk_of_bias, cost_effectiveness_model, etc.) default to "standard". Pass ai_disclosure_level: "off" to suppress.
来源
awesome · https://github.com/neptun2000/heor-agent-mcp
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