Baixiaoying Mcp Server(全球最强医疗循证模型、可信医疗内容搜索)

Created By
百川智能@Andy4 months ago
百川智能发布的基于全球最强医疗增强模型Baichuan M3 Plus构建的MCP Server,全网第一批完整支持MCP APPs协议,提供可视化的回答内容,体验完全对标百川官方严肃医疗 APP 百小应。
Overview

中文 | English

@baichuan-ai/baixiaoying-mcp-server

npm version License MCP Apps

百小应医学大模型 MCP Server —— 已支持 MCP 协议最新 Feature MCP APPs,提供可视化的回答内容,体验完全对标百川官方 APP 百小应

Baichuan-M3-Plus

为什么选择百小应 MCP Server?

🏆 SOTA 医学大模型

Baichuan-M3-Plus 是百川智能推出的最低幻觉循证增强医疗大模型,在权威医学评测中表现卓越:

指标表现
幻觉率基准测试仅 2.6%,大幅领先行业
HealthBench超越 OpenAI GPT-5.2,达到 SOTA
HealthBench-Hard得分 44.4,超越 GPT-5.2
SCAN-bench唯一在 Clinical Inquiry、Laboratory Testing、Diagnosis 三项同时排名第一
成本相比上一代模型降低 70%

🧬 核心技术优势

  • 六源循证系统 - 首创证据锚定技术,回答严谨可追溯,有效抑制幻觉
  • 临床问诊思维 - 模型底层具备临床医生的问诊思维与循证思维,支持 SCAN-Driven Clinical-Grade Systematic History Taking
  • 高保真临床问诊 - High-Fidelity Clinical Inquiry,将问诊过程重构为临床级别、结构化、可审计的信息生成流水线

🧩 MCP APPs 协议

已支持 MCP 最新协议 MCP APPs,输出可视化内容,效果与百小应官方 APP 完全对齐:

百小应可视化回答示例 百小应引用与证据示例

功能特性

  • 🖥️ 可视化回答 - 输出可视化内容,效果与百小应官方 APP 对齐
  • 🩺 医学问答对话 - 使用专业医学大模型回答健康相关问题
  • 📄 文档问答 - 上传医学文档进行智能问答
  • 📚 证据引用 - 回答附带专业文献引用
  • 🧠 思考过程 - 展示模型的推理思考步骤
  • 🔌 多协议支持 - 支持 stdio、SSE、Streamable HTTP、Hybrid 四种传输模式
  • 🚀 服务器部署 - 支持独立部署为 HTTP 服务,可供多客户端同时访问

📋 应用场景

百小应背后拥有权威的医疗专业知识库,涵盖临床指南、药品说明书、医学文献等海量权威数据源,并保持动态更新。无论是日常问诊、临床决策还是医学研究,都能提供最可靠、可信的专业回答。

🩺 智能问诊

模拟临床医生的问诊思维,进行系统化的病史采集和症状分析。

我最近总是头晕,尤其是早上起床的时候,站起来会眼前发黑,持续大概几秒钟。请帮我分析一下可能的原因?
孩子 3 岁,昨天开始发烧 38.5°C,伴有流鼻涕和轻微咳嗽,精神状态还可以,需要去医院吗?

💊 药物分析

深度解析药物成分、作用机制、适应症及不良反应。

帮我分析一下阿司匹林和布洛芬的区别,它们的作用机制有什么不同?
二甲双胍的作用机制是什么?为什么它是 2 型糖尿病的一线用药?

💉 用药指导

提供专业的用药建议,包括剂量、用法、注意事项及药物相互作用。

我正在服用华法林,医生又给我开了阿莫西林,这两种药可以一起吃吗?需要注意什么?
老年高血压患者长期服用氨氯地平,有哪些需要注意的事项?

📖 指南查询

快速检索最新临床诊疗指南,获取权威推荐意见。

2024 年中国高血压防治指南对于高血压的诊断标准和分级是怎么规定的?
最新的糖尿病肾病临床诊疗指南中,推荐的一线降糖药物是什么?

🏥 治疗方案

基于循证医学,提供个性化的治疗方案建议。

初诊 2 型糖尿病患者,空腹血糖 9.2mmol/L,糖化血红蛋白 8.1%,BMI 26,无明显并发症,应该如何制定治疗方案?
社区获得性肺炎的经验性抗菌治疗方案有哪些选择?

🔬 诊断分析

辅助分析检验检查结果,提供鉴别诊断思路。

患者肝功能检查显示 ALT 156 U/L,AST 89 U/L,GGT 正常,请帮我分析可能的原因和需要进一步做的检查。
甲状腺功能检查 TSH 偏低,FT4 偏高,这提示什么问题?需要做哪些进一步检查?

📚 医学研究动态

追踪医学领域最新研究进展和突破性成果。

GLP-1 受体激动剂在心血管保护方面有哪些最新的研究进展?
CAR-T 细胞疗法在实体瘤治疗中的最新研究突破有哪些?

✍️ 医学写作辅助

辅助医学论文写作、病历书写、医学翻译等专业文档工作。

帮我写一份急性心肌梗死的入院病历模板,包括主诉、现病史、既往史等要素。
请帮我将这段临床研究摘要翻译成规范的医学英语。

🎁 海纳百川计划

海纳百川计划

百川正式推出「海纳百川」计划,面向所有为医务工作者提供服务的机构,免费提供循证增强的 M3-Plus API

参与条件

项目说明
适用对象为医务工作者提供服务的机构(医生、药剂师、医技师、护士、健管师、医学生等)
适用场景临床辅助决策、医学教育
用途限制仅用于真实服务场景,不得用于数据生产
使用要求产品需明确展示 Powered by 百川,不得对模型输出进行影响准确性的修改

👉 立即申请

支持的模型

模型说明
Baichuan-M3-Plus最新医学大模型,推荐使用
Baichuan-M2-Plus医学大模型

学术与资源

快速开始

前置条件

百川开放平台 获取 API Key。

方式一:一键安装(推荐)

我们在每个 GitHub Release 中提供 .dxt.mcpb 两种安装包,下载后双击即可安装,无需任何命令行操作。

格式说明支持的客户端
.dxtDesktop Extension,Cursor 专用的 MCP 扩展格式Cursor
.mcpbMCP Bundle,MCP 官方标准打包格式,类似 Chrome 扩展(.crx),将 MCP Server 及其依赖打包为可直接安装的 ZIP 归档Claude Desktop、Claude Code

前往 GitHub Releases 下载最新版本的安装包。

方式二:使用官方 SSE 服务(零部署)

百川提供官方托管的 SSE 服务,无需本地安装和部署,直接在客户端中配置即可使用。

Cursor 配置 — 在 ~/.cursor/mcp.json 中添加:

{
  "mcpServers": {
    "baixiaoying": {
      "type": "sse",
      "url": "https://baixiaoying-mcp-server.baichuan-ai.com/sse",
      "headers": {
        "Authorization": "Bearer your-baichuan-api-key"
      }
    }
  }
}

your-baichuan-api-key 替换为你的百川 API Key。

方式三:npx 快速启动

适用于 Claude Desktop 等 stdio 模式客户端,在配置文件 claude_desktop_config.json 中添加:

{
  "mcpServers": {
    "baixiaoying": {
      "command": "npx",
      "args": ["-y", "@baichuan-ai/baixiaoying-mcp-server"],
      "env": {
        "BAICHUAN_API_KEY": "your-api-key-here"
      }
    }
  }
}

更多安装方式(npm 安装、服务器部署、Docker、环境变量配置等)请参阅 开发指南

可用工具

详细文档请参阅 可用工具

工具说明
baixiaoying_chat使用百小应大模型进行医学问答对话
baixiaoying_upload_file上传医学文档用于文档问答
baixiaoying_list_files获取已上传的文件列表
baixiaoying_get_file_status查询文件解析状态
baixiaoying_delete_file删除已上传文件

开发

详细文档请参阅 开发指南

许可证

Apache License 2.0

Server Config

{
  "mcpServers": {
    "baixiaoying": {
      "type": "sse",
      "url": "https://baixiaoying-mcp-server.baichuan-ai.com/sse",
      "headers": {
        "Authorization": "Bearer your-baichuan-api-key"
      }
    }
  }
}
Project Info
Created At
4 months ago
Updated At
4 months ago
Author Name
百川智能@Andy
Star
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Run pqc_stig to assess your project's quantum readiness against PQC-01-STIG-V1R1 — the World's First DoD-style Post-Quantum Cryptography STIG — no license key needed. What It Does KHEPRA MCP connects your AI assistant directly to a hardened compliance engine. Ask Claude or any MCP client to scan a system, map findings to STIG/NIST/CMMC controls, and generate an executive-ready risk report — all without sending data to external APIs. Key capabilities: 36,195 STIG/CCI/NIST 800-53/800-171/CMMC mappings (offline, bundled) Post-quantum cryptographic attestation on every tool call (ML-DSA-65 / FIPS 204) World's First DoD PQC STIG — 17 controls covering CNSA 2.0 / FIPS 203/204/205 + agentic AI / MCP (PQC-01-STIG-V1R1) Godfather Report: dollar-denominated business impact per finding (FAIR model) Air-gap and SCIF compatible — sovereign/ironbank modes make zero egress calls Flat annual licensing — no per-token or per-query charges Runs on your metal: on-prem, DoD, IC, classified environments Installation There are two delivery methods: Docker (recommended, no build required) and compiled binary (fastest startup, required for air-gap). Both support the same environment variables and all MCP clients. Choose your path: Method Best For Startup Docker Most users, easiest setup ~2s Compiled Binary Air-gap, SCIF, performance ~300ms Option A: Docker (Recommended) Requires Docker Desktop or Docker Engine. The image is pre-built and ships the full compliance database — no additional downloads in sovereign mode. # Pull once docker pull ghcr.io/nouchix/pqc-khepra-mcp:latest # Test it (should print the initialize response and exit) echo '{"jsonrpc":"2.0","method":"initialize","params":{"protocolVersion":"2025-11-25","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}},"id":0}' \ | docker run --rm -i -e KHEPRA_MODE=sovereign ghcr.io/nouchix/pqc-khepra-mcp:latest Option B: Compiled Binary Requires Go 1.21+ for building, or download a pre-built release from GitHub Releases. git clone https://github.com/nouchix/PQC-Khepra-MCP.git cd PQC-Khepra-MCP # Build (cross-compile for your OS) go build -o khepra-mcp ./cmd/khepra-mcp # Linux / macOS go build -o khepra-mcp.exe ./cmd/khepra-mcp # Windows # Test the binary echo '{"jsonrpc":"2.0","method":"initialize","params":{"protocolVersion":"2025-11-25","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}},"id":0}' \ | KHEPRA_MODE=sovereign ./khepra-mcp Windows — using the batch launcher The repo ships a run-mcp.bat launcher for Windows. It uses the pre-built binary (fast path) and falls back to go run automatically: :: run-mcp.bat is already in the repo at the root of PQC-Khepra-MCP :: Point your MCP client to: cmd /c C:\path\to\PQC-Khepra-MCP\run-mcp.bat Adding to Your AI Client Claude Desktop Config file location: macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json Linux: ~/.config/Claude/claude_desktop_config.json Community tier — Docker (macOS / Linux) { "mcpServers": { "khepra": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "KHEPRA_MODE=sovereign", "-v", "/var/lib/khepra:/var/lib/khepra", "ghcr.io/nouchix/pqc-khepra-mcp:latest" ] } } } Community tier — Docker (Windows) { "mcpServers": { "khepra": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "KHEPRA_MODE=sovereign", "-v", "C:\\Users\\YourName\\.khepra:/var/lib/khepra", "ghcr.io/nouchix/pqc-khepra-mcp:latest" ] } } } Community tier — Binary (Windows, fastest startup) { "mcpServers": { "khepra": { "command": "C:\\path\\to\\PQC-Khepra-MCP\\khepra-mcp.exe", "args": [], "env": { "KHEPRA_MODE": "sovereign", "KHEPRA_NETWORK_POLICY": "lan", "MCP_PQC_ENABLED": "true", "KHEPRA_MANIFEST_PATH": "C:\\path\\to\\PQC-Khepra-MCP\\manifest.json" } } } } Community tier — Binary via batch launcher (Windows) { "mcpServers": { "khepra": { "command": "cmd", "args": ["/c", "C:\\path\\to\\PQC-Khepra-MCP\\run-mcp.bat"], "env": { "KHEPRA_MODE": "sovereign", "KHEPRA_NETWORK_POLICY": "lan", "MCP_PQC_ENABLED": "true" } } } } Sovereign / Pharaoh tier (with license key) { "mcpServers": { "khepra": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "KHEPRA_LICENSE_KEY", "-e", "KHEPRA_MODE=sovereign", "-v", "/var/lib/khepra:/var/lib/khepra", "-v", "/var/log/khepra:/var/log/khepra", "ghcr.io/nouchix/pqc-khepra-mcp:latest" ], "env": { "KHEPRA_LICENSE_KEY": "YOUR_LICENSE_KEY_HERE" } } } } After editing, restart Claude Desktop. Verify in Settings → Developer — you should see khepra with status running and all tools listed. Cursor Config file: .cursor/mcp.json in your project root, or ~/.cursor/mcp.json globally. Docker (macOS / Linux) { "servers": { "khepra": { "type": "stdio", "command": "docker", "args": [ "run", "--rm", "-i", "-e", "KHEPRA_MODE=sovereign", "-v", "/var/lib/khepra:/var/lib/khepra", "ghcr.io/nouchix/pqc-khepra-mcp:latest" ] } } } Binary (macOS / Linux) { "servers": { "khepra": { "type": "stdio", "command": "/path/to/khepra-mcp", "args": [], "env": { "KHEPRA_MODE": "sovereign", "KHEPRA_MANIFEST_PATH": "/path/to/PQC-Khepra-MCP/manifest.json" } } } } Binary (Windows) { "servers": { "khepra": { "type": "stdio", "command": "C:\\path\\to\\PQC-Khepra-MCP\\khepra-mcp.exe", "args": [], "env": { "KHEPRA_MODE": "sovereign", "KHEPRA_MANIFEST_PATH": "C:\\path\\to\\PQC-Khepra-MCP\\manifest.json" } } } } VS Code (with GitHub Copilot or Cline extension) Config file: .vscode/mcp.json in your project, or user settings. { "servers": { "khepra": { "type": "stdio", "command": "docker", "args": [ "run", "--rm", "-i", "-e", "KHEPRA_MODE=sovereign", "-v", "${env:HOME}/.khepra:/var/lib/khepra", "ghcr.io/nouchix/pqc-khepra-mcp:latest" ] } } } Or via user settings.json for the Cline extension: { "cline.mcpServers": { "khepra": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "KHEPRA_MODE=sovereign", "ghcr.io/nouchix/pqc-khepra-mcp:latest" ] } } } Windsurf Config file: ~/.codeium/windsurf/mcp_config.json { "mcpServers": { "khepra": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "KHEPRA_MODE=sovereign", "-v", "/var/lib/khepra:/var/lib/khepra", "ghcr.io/nouchix/pqc-khepra-mcp:latest" ] } } } Continue.dev Config file: ~/.continue/config.json — add to the experimental.modelContextProtocolServers array: { "experimental": { "modelContextProtocolServers": [ { "name": "khepra", "transport": { "type": "stdio", "command": "docker", "args": [ "run", "--rm", "-i", "-e", "KHEPRA_MODE=sovereign", "ghcr.io/nouchix/pqc-khepra-mcp:latest" ] } } ] } } Cloud / SaaS AI Tools (Claude.ai, ChatGPT, Gemini, etc.) Cloud-based AI tools cannot directly spawn local subprocesses — they need an HTTP/SSE bridge to reach your local KHEPRA server. There are two approaches: Approach 1 — mcp-remote proxy (easiest, no server required) mcp-remote tunnels a local stdio MCP server over HTTPS, making it accessible to any cloud tool. This is what the Kaggle MCP entry in the config above uses. # Install once npm install -g mcp-remote # Start the bridge (exposes your local KHEPRA server at https://localhost:3000) KHEPRA_MODE=sovereign mcp-remote \ --server "docker run --rm -i -e KHEPRA_MODE=sovereign ghcr.io/nouchix/pqc-khepra-mcp:latest" \ --port 3000 Then in Claude.ai (or any cloud tool that accepts MCP SSE URLs): MCP Server URL: http://localhost:3000/sse Security note: mcp-remote binds to localhost by default. Do not expose it to the public internet without TLS and authentication. In sovereign/ironbank mode, KHEPRA itself makes zero egress calls — only the bridge connection to the cloud tool carries data. Approach 2 — Self-hosted HTTP/SSE endpoint For teams running KHEPRA on a shared server (e.g., Hostinger VPS at IP_ADDRESS), start the server in HTTP mode: # On your server — start KHEPRA in HTTP/SSE mode docker run -d \ -e KHEPRA_MODE=hybrid \ -e KHEPRA_HTTP_PORT=8443 \ -e KHEPRA_LICENSE_KEY="${KHEPRA_LICENSE_KEY}" \ -p 8443:8443 \ ghcr.io/nouchix/pqc-khepra-mcp:latest # Point your cloud tool to: # https://your-server.com:8443/sse Then configure any cloud AI tool that supports MCP SSE: Cloud Tool Where to add MCP URL Claude.ai (Pro/Team) Settings → Integrations → MCP Servers OpenAI Assistants API tools field with type: "mcp" Gemini for Workspace Extensions → Custom MCP (preview) Glama.ai Workspace → MCP Servers Smithery.ai Catalog → Self-hosted server Note: HTTP/SSE mode (hybrid/edge) enables external connections. Always terminate TLS at a reverse proxy (nginx/Caddy) and restrict access by IP or API key. The sovereign mode refuses HTTP connections by design — air-gap integrity is preserved. Approach 3 — Smithery / MCP Registry (Community tier only) KHEPRA is listed on Smithery.ai and the MCP Registry. Cloud tools that support registry-based discovery can install it directly: Registry ID: io.github.nouchix/pqc-khepra-mcp This runs the Community tier via Smithery's managed infrastructure. For sovereign deployment (air-gap, your data stays on your metal), use Options A or B above. Validation — Test Your Installation Run this from your terminal to verify the server responds correctly: # Docker echo '{"jsonrpc":"2.0","method":"tools/list","params":{},"id":1}' \ | docker run --rm -i -e KHEPRA_MODE=sovereign ghcr.io/nouchix/pqc-khepra-mcp:latest # Binary (Linux / macOS) echo '{"jsonrpc":"2.0","method":"tools/list","params":{},"id":1}' \ | KHEPRA_MODE=sovereign ./khepra-mcp # Binary (Windows PowerShell) '{"jsonrpc":"2.0","method":"tools/list","params":{},"id":1}' \ | & ".\khepra-mcp.exe" Expected output: a JSON-RPC response listing all available tools. If you see "tools": [...] with 12+ entries — you're connected. Full protocol validation (Windows) # Runs the complete Claude Desktop handshake sequence and validates all responses .\scripts\test-mcp-handshake.ps1 -BinaryPath ".\khepra-mcp.exe" # Expected output: # [PASS] initialize | protocolVersion=2025-11-25 | listChanged=False # [PASS] tools/list | count=34 # TRL-10 READY - Server passes full Claude Desktop protocol validation MCP Tools Community Tier (Free — No License Key) pqc_stig — World's First DoD PQC STIG ⭐ Assesses a source code directory against PQC-01-STIG-V1R1: 12 controls covering CNSA 2.0 algorithm approval, ML-DSA-65 key strength, ML-KEM-768 encapsulation, hybrid cryptography, key storage, constant-time implementation, and certificate chain requirements. pqc_stig(scan_path?: string, profile?: "quick" | "full" | "executive") Example: "Run pqc_stig on my project and tell me if I'm CNSA 2.0 compliant" nist_map Map CCI identifiers or STIG findings to NIST 800-53 Rev 5 controls. khepra_query_stig Query the 36,195-row STIG/CCI/NIST/CMMC compliance database by control ID. dark_crypto_contribute (opt-in) Contribute anonymized cryptographic algorithm telemetry to the SouHimBou AI Dark Crypto Intelligence Network. No PII. Opt-in only — never fires without explicit invocation. Sovereign / Pharaoh Tier ert_scan Enterprise Risk & Threat scan across STIG, NIST 800-53, NIST 800-171, CMMC, and FedRAMP. Returns Godfather Report with dollar-denominated business impact. ert_scan(target: string, frameworks?: string[], output_format?: "godfather" | "json" | "csv") Example: "Run ert_scan on /etc and generate a Godfather Report" stig_check Automated RHEL-09-STIG-V1R3 compliance scan against a live system or configuration path. cmmc_assess Full CMMC Level 1, 2, or 3 assessment with gap analysis and POA&M generation. godfather_report Generate an executive Godfather Report from prior scan results: top 10 findings ranked by dollar exposure, remediation ROI, and FAIR model business impact. + 20 additional tools agent_record, dag_attestation, flight_export, khepra_get_dag_chain, nhi_inventory, acp_status, owasp_agent_assess, khepra_export_attestation, khepra_export_poam, khepra_get_compliance_score, ert_crypto, ert_readiness, stig_benchmark, ir_analysis, vuln_hunter, sbom_generate, threat_model, khepra_query_threat_intel, discover_assets, and more. The Godfather Report Unlike compliance scanners that output a wall of CVEs, KHEPRA translates findings into the language executives care about: Finding: RHEL-09-212030 — No FIPS-validated crypto on /etc/ssh Severity: CAT I (HIGH) Business Impact: $2.4M estimated breach exposure (FAIR model) Remediation Cost: $800 (4 hours engineer time) ROI: 3,000x Every finding includes control ID, framework mapping, business impact in dollars, remediation cost estimate, and ROI. Deployment Modes Mode Air-Gap Egress Telemetry Use Case sovereign ✅ Yes Zero Zero On-prem, SCIF, classified (DEFAULT) ironbank ✅ Yes Zero Zero DoD/IC production, FIPS-only hybrid ❌ No LAN Zero Edge + cloud coordination edge ❌ No Unrestricted Zero Fully stateless SaaS Set via KHEPRA_MODE environment variable. Unknown values are rejected at startup and fall back to sovereign (fail-closed). Environment Variables Variable Required Default Description KHEPRA_LICENSE_KEY Sovereign/Pharaoh only — License key. Community tier runs without one. Get at nouchix.com KHEPRA_MODE No sovereign Deployment mode: sovereign, ironbank, hybrid, edge KHEPRA_MANIFEST_PATH No manifest.json Path to signed tool manifest file KHEPRA_HOME No /var/lib/khepra Data and compliance DB directory KHEPRA_LOG_DIR No /var/log/khepra Log directory KHEPRA_DAG_PATH No ~/.khepra/dag DAG audit chain storage path KHEPRA_AUDIT_LOG_PATH No ~/.khepra/audit.ndjson Signed audit log path KHEPRA_MAX_CONCURRENT No 5 Max concurrent tool calls per agent KHEPRA_NETWORK_POLICY No lan Network scope: lan, none, unrestricted MCP_PQC_ENABLED No true Enable ML-DSA-65 PQC attestation on all responses Air-Gap & SCIF Deployment KHEPRA makes zero external network calls in sovereign and ironbank modes: License validated offline via ML-DSA-65 signed license.adinkhepra file Compliance databases (36,195 mappings) bundled in container — no external downloads No telemetry, no heartbeat, no egress — verified at the transport layer # Transfer image to air-gapped network docker save ghcr.io/nouchix/pqc-khepra-mcp:latest | gzip > khepra-mcp.tar.gz # On air-gapped host: docker load < khepra-mcp.tar.gz Note on telemetry: The dark_crypto_contribute tool (Community tier) sends anonymized cryptographic algorithm telemetry to the SouHimBou AI intelligence network only when explicitly invoked by the user. It is never triggered automatically. In sovereign/ironbank mode, all network calls are blocked at the transport layer regardless. Compliance Coverage Framework Version Mappings STIG (RHEL 9) V1R3 Automated scanning NIST 800-53 Rev 5 2,120 CCIs NIST 800-171 Rev 2 320 controls CMMC Level 3 Full practice set FedRAMP High Baseline scanning PQC-01-STIG-V1R1 V1R1 17 PQC controls (CNSA 2.0) Total 36,195+ mappings Licensing Flat annual licensing — no per-token or per-query charges. Tier Cost License Key Tools Community Free Not required pqc_stig + 12 core tools Sovereign Annual flat fee Required All 34 tools, air-gap, on-prem Pharaoh Annual flat fee Required All 34 tools + priority support + SLA Community tier is permanently free — contribute to open-source PQC adoption Sovereign/Pharaoh: contact contact@nouchix.com or visit nouchix.com Security Reporting Vulnerabilities Do not open public issues for security vulnerabilities. Report privately via GitHub Security Advisories or email support@nouchix.com. SLA Target Acknowledgement 24 hours Initial assessment 5 business days Patch / mitigation (Critical) 30 days We accept encrypted reports via PGP (keys/security_contact.asc) and Post-Quantum channels (Dilithium / ML-DSA-65 keys in keys/). See SECURITY.md for the full disclosure policy and ASAF event taxonomy. Security Posture Deploying advanced post-quantum cryptography, air-gapped isolation, and comprehensive STIG mappings — built in direct alignment with NSA & ASD Model Context Protocol guidelines. NSA & ASD MCP Security Alignment The NSA and Australian Signals Directorate (ASD) have published specific threat vectors for AI systems interacting with local environments. KHEPRA MCP is explicitly designed to mitigate every identified vector: NSA/ASD Requirement KHEPRA Implementation Cryptographic validation of tool responses ML-DSA-65 (Dilithium) signatures on all JSON-RPC 2.0 payloads Input validation & sanitization Parameter injection resistance via strict JSON Schema validation Principle of least privilege credentials Short-lived ephemeral tokens tied to specific task execution windows Comprehensive audit logging Tamper-evident events compiled into an immutable DAG structure Resource consumption limits Rate limiting + backpressure for LLM request loops Authorization gates for sensitive actions Human-in-the-loop gate for destructive state changes Environment isolation Containerized execution with zero-egress sovereign mode Software supply chain integrity Manifest pinning for all loaded tools and dependencies Network exposure reduction Air-gappable — zero internet transit in sovereign/ironbank modes Post-quantum resilience PQC-signed DAG trail protecting against harvest-now-decrypt-later Compliance Certifications Framework Status Coverage CMMC Level 2 ✅ Automates evidence collection for AU, CM, SI, SC domains NIST SP 800-171 Rev 2 ✅ Logging, accountability, system integrity NIST SP 800-53 Rev 5 ✅ Continuous monitoring (AU-2, SI-4) FIPS 203 (ML-KEM) ✅ Key encapsulation for secure transit FIPS 204 (ML-DSA) ✅ Digital signatures for payload authentication NSM-10 PQC Mandate ✅ National Security Memorandum 10 compliance DFARS 252.204-7012 ✅ Immutable forensic trails for cyber incident reporting NSA MCP Security Guidelines ✅ Direct mapping to all published AI agent threat mitigations Live Deployment — Physical Edge Running continuously on constrained edge hardware since May 12, 2026 to prove efficiency in sovereign environments: Hardware: Raspberry Pi 2 · 1 GB RAM · 900 MHz ARM · Live Spectrum Router SCADA Pod: STM32U585 / QRB2210 · Modbus TCP · MQTT · Zephyr RTOS 3.4+ · Live Dilithium Signature Verification Controls active: 3 open ports secured · 12 STIG violations detected · 100% file integrity monitoring (AIDE) · 24/7 continuous operation Academic Validation Event Date Institution UAlbany AI Plus Symposium 2026 — "KHEPRA Protocol: Quantum-Resilient Agentic

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