medharness — MCP Server by charliehzm

by charliehzm · MCP Server · ★ 101

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About medharness

MedHarness · 医疗大模型流量安全与合规网关 给医院、医疗信息化厂商和医疗 AI 团队用的大模型统一出口: 每一次模型调用先过患者敏感信息识别、脱敏、分级路由、出站检查和审计留痕,再转发给允许的模型。 开源 · 支持私有化/专有云部署 · 面向中国医疗数据合规场景 (个人信息保护法 PIPL · 数据安全法 · 网络安全法/等保 · 健康医疗数据安全指南,兼顾 HIPAA) 说明:下文少量出现的 PHI 指患者健康医疗相关敏感信息,包括身份标识、就诊记录、检查检验、影像、诊断、用药等。 一句话:它是什么 HIS、EMR、CDR、互联网医院、随访系统、Dify/RAG/Agent,或者研发工具,只要把 指向 MedHarness, 每一次大模型调用都会先经过一条强制合规闸门: 识别患者敏感信息 → 脱敏 → 数据分级签名 → 模型白名单路由 → 提示注入扫描 → 出站安全检查 → 全量审计。 任一环节不确定或判定有风险,就直接拒绝,不连接上游模型。 它不是又一个通用大模型网关(LLM Gateway)。通用网关解决“接模型、限流、计费”,MedHarness 解决医疗场景里更关键的三件事: 患者数据能不能出、能出给哪个模型、出了事能不能查清楚。 HIS · EMR · CDR · 互联网医院 · Dify · RAG · Agent · 研发工具 │ OpenAI / Claude 兼容协议 —— 改 baseurl ▼ ┌──────────────────────────────────┐ │ MedHarness 合规网关 │ │ 识别→脱敏→分级→路由→注入→[转发]→出站→审计 │ └──────────────────────────────────┘ │ 脱敏后 · 白名单内 · 全链路留痕 ▼

ai-codingclaude-codecompliancehealthcarehipaamcpmedicalopenspecphipipl

Quick Facts

Stars101
Forks8
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score60.1269319658675/100
Open Issues11
Last Updated2026-06-05
Created2026-05-20
Platformsclaude-code, mcp, python
Est. Tokens~1071k

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Frequently Asked Questions

What is medharness?

medharness is 让医疗机构所有大模型流量:PHI 不外泄 · 模型走白名单 · 全量可审计 · 成本可控。. It is categorized as a MCP Server with 101 GitHub stars.

What programming language is medharness written in?

medharness is primarily written in Python. It covers topics such as ai-coding, claude-code, compliance.

How do I install or use medharness?

You can find installation instructions and usage details in the medharness GitHub repository at github.com/charliehzm/medharness. The project has 101 stars and 8 forks, indicating an active community.

What license does medharness use?

medharness is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to medharness?

The top alternatives to medharness on Agent Skills Hub include spec-superflow, claude-context-local, claude-code-open. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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