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Nist Rmf Ai MCP server. Tools: assess risk profile, map ai impact, generate risk controls. Built by MEOK AI Labs.

Project description

nist-rmf-ai-mcp MCP server

PyPI Downloads GitHub stars License: MIT

NIST AI RMF MCP

NIST AI Risk Management Framework (AI 100-1) implementation across all four functions: GOVERN, MAP, MEASURE, MANAGE. Risk profiling, trustworthy AI characteristics, and EU AI Act crosswalk.

MEOK AI Labs

Install · Tools · Pricing · Attestation API


Why This Exists

NIST AI 100-1 is the de facto AI risk management standard for US federal agencies, federal contractors, and any US-headquartered company building AI governance. Executive Order 14110 (Oct 2023) directs federal agencies to adopt the AI RMF, and procurement officers increasingly require AI RMF compliance documentation from vendors.

The framework defines four core functions (GOVERN, MAP, MEASURE, MANAGE) with 19 categories and 72 subcategories. Mapping your AI system against all of them, assessing trustworthy AI characteristics (valid, reliable, safe, secure, accountable, transparent, explainable, privacy-enhanced, fair), and crosswalking to EU AI Act for dual-jurisdiction compliance is time-intensive. This MCP automates the full assessment.

Install

pip install nist-rmf-ai-mcp

Tools

Tool AI RMF Reference What it does
assess_risk_profile GOVERN, MAP, MEASURE, MANAGE Full risk profile assessment across all 4 functions
map_ai_impact MAP 1-5 Map AI system context, impacts, and stakeholders
generate_risk_controls MANAGE 1-4 Generate risk response and control recommendations
crosswalk_to_eu_ai_act AI RMF + EU AI Act Map NIST AI RMF subcategories to EU AI Act requirements
create_risk_report All functions Generate a structured AI risk management report
check_trustworthy_characteristics AI RMF Core Evaluate against NIST trustworthy AI characteristics
predict_risk_neural ML-assisted Neural network risk prediction for AI systems
quick_scan All functions Rapid AI system risk overview
framework_overview AI 100-1 Full framework structure and reference guide

Example

Prompt: "Assess our healthcare diagnostic AI against the NIST AI RMF.
It analyses chest X-rays, was trained on NIH ChestX-ray14, deployed
in a US hospital network, and clinicians use it as a second opinion."

Result: Assessment across all 4 functions with findings: MAP identifies
high-impact healthcare context with patient safety implications, MEASURE
flags dataset bias risk (ChestX-ray14 demographic skew), MANAGE requires
human-in-the-loop validation controls, GOVERN needs AI governance board
oversight. Trustworthy AI assessment scores each characteristic.

Pricing

Tier Price What you get
Free £0 10 calls/day — risk profile + quick scan
Pro £199/mo Unlimited + HMAC-signed attestations + verify URLs
Enterprise £1,499/mo Multi-tenant + co-branded reports + webhooks

Subscribe to Pro · Enterprise

Attestation API

Every Pro/Enterprise audit produces a cryptographically signed certificate:

POST https://meok-attestation-api.vercel.app/sign
GET  https://meok-attestation-api.vercel.app/verify/{cert_id}

Zero-dep verifier: pip install meok-attestation-verify

Links

License

MIT

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