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ISO 27001 AI - MCP server providing AI-powered tools and automation by MEOK AI Labs
ISO 27001 AI - MCP server providing AI-powered tools and automation by MEOK AI Labs
⚖️ Built by MEOK AI Labs / CSOAI. Need this applied to your system fast? Book a 30-min Founder Office Hour (£29) → https://meok.ai/work · Full governance platform → https://meok.ai
MEOK AI Labs EU AI Act License PyPI
MEOK AI Labs MCP Server
MEOK AI Labs MCP Server
# Install via pip
pip install iso_27001_ai_mcp
# Or install via Smithery
npx -y @smithery/cli@latest install iso-27001-ai-mcp --client claude
This MCP server is built with EU AI Act compliance built-in:
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This server is part of the MEOK AI Labs ecosystem — 300+ MCP servers for sovereign AI governance.
| Domain | Purpose |
|---|---|
| councilof.ai | EU AI Act compliance marketplace |
| safetyof.ai | AI safety & monitoring |
| meok.ai | Sovereign AI platform |
| cobolbridge.ai | Legacy modernization |
MIT © CSOAI-ORG
Built with 💜 by MEOK AI Labs · UK Companies House 16939677
mcp-name: io.github.CSOAI-ORG/iso-27001-ai-mcpISO/IEC 27001:2022 compliance assessment for AI systems — 93 Annex A controls across 4 themes, ISO 27005 risk assessment, Statement of Applicability generation, incident classification, and ISO 42001 bridge.
PyPI npm License: MIT smithery
ISO/IEC 27001:2022 is the international standard for Information Security Management Systems (ISMS). Its Annex A contains 93 controls organized into 4 themes: Organizational (37 controls), People (8), Physical (14), and Technological (34). Certification requires demonstrating that your ISMS meets clauses 4–10 and that your Statement of Applicability (SoA) addresses all relevant controls.
For AI systems, ISO 27001 is foundational — but it needs extension. This server audits your ISMS against all 93 controls, performs ISO 27005 risk assessments with AI-specific threat scenarios, generates gap analyses with prioritized remediation roadmaps, produces SoAs, classifies security incidents, and bridges to ISO 42001 for AI-specific governance.
npx meok-setup --pack governance
| Tool | Description | Parameters |
|---|---|---|
audit_isms |
Audits your ISMS against all 93 Annex A controls. Returns per-theme compliance status (PASS/PARTIAL/FAIL), gap identification, critical gap flagging for high-priority controls (A.5.1, A.5.15, A.8.5, A.8.24, etc.), and certification readiness assessment. | organization_context, scope_description, controls_implemented |
risk_assessment |
Performs ISO 27005 information security risk assessment. Evaluates 10 AI-relevant threat categories (adversarial attacks, model theft, training data breach, supply chain compromise, insider threat, etc.), calculates likelihood × impact risk scores, and produces a treatment plan with specific Annex A control recommendations. | system_description, assets, threat_scenarios, existing_controls |
gap_analysis |
Compares your current controls to ISO 27001 requirements. Supports three targets: "full" (all 93 controls), "core" (critical subset), or "ai-focused" (AI-relevant controls only). Returns prioritized remediation roadmap in 3 phases: Critical (0–30 days), Standard (30–90 days), Remaining (90–180 days). | current_controls, target_certification, focus_themes |
crosswalk_to_ai |
Maps ISO 27001 controls to ISO 42001 AI-specific requirements. Shows how existing ISMS controls extend to AI governance (model security, training data protection, AI incident management) and identifies where AI-specific controls are needed. | controls, focus_area |
generate_soa |
Generates a Statement of Applicability per clause 6.1.3(d). Documents all 93 controls as Implemented, Excluded (with justification), or Not Yet Addressed. Required artifact for ISO 27001 certification audits. | organization_name, controls_implemented, controls_excluded, exclusion_justifications |
incident_classification |
Classifies security incidents per controls A.5.24–A.5.28. Determines severity (LOW→CRITICAL), priority (P1–P3), notification requirements, and response procedures. Includes AI-specific incident categories: adversarial attacks, data poisoning, model theft, prompt injection, bias incidents. | incident_description, affected_assets, detection_method, data_breach, ai_system_involved |
Use the audit_isms tool with:
organization_context: "AI startup with 150 employees building ML models for healthcare diagnostics. Uses AWS for infrastructure, processes patient data, has a small security team."
scope_description: "All AI systems, ML pipelines, patient data processing, cloud infrastructure, and development environments"
controls_implemented: ["A.5.1", "A.5.9", "A.5.12", "A.5.15", "A.5.24", "A.6.3", "A.8.5", "A.8.7", "A.8.8", "A.8.15", "A.8.24"]
Expected output: Overall coverage ~12% (11/93 controls). Critical gaps flagged in A.5.34 (PII protection), A.8.12 (data leakage prevention), A.8.25 (secure SDLC). Certification NOT ready — 82 gaps to address.
Use the risk_assessment tool with:
system_description: "Production ML pipeline processing financial data for fraud detection. Uses gradient boosting models trained on 10M+ transaction records. Served via REST API with 99.9% SLA."
assets: ["training data", "ML model weights", "feature store", "API keys", "model serving infrastructure", "customer transaction data"]
existing_controls: ["A.5.15", "A.8.5", "A.8.15", "A.8.24"]
Expected output: Risk register with 10 threat assessments. Highest risks: training data breach (likely × high = risk score 16), model theft (possible × critical = 20). Treatment plan recommends implementing A.8.12, A.8.16, A.5.12 for the highest-priority gaps.
Use the gap_analysis tool with:
current_controls: ["A.5.1", "A.5.2", "A.5.15", "A.5.24", "A.6.3", "A.8.5", "A.8.7", "A.8.15", "A.8.16", "A.8.24"]
target_certification: "ai-focused"
Expected output: 25 AI-critical controls evaluated. ~40% coverage. Phase 1 critical gaps: A.8.8 (vulnerability management), A.8.12 (data leakage), A.5.34 (PII protection). Estimated remediation: 3–6 months.
Use the incident_classification tool with:
incident_description: "Adversarial evasion attack detected on production fraud detection model. Attackers crafted transactions that bypassed ML model scoring. Approximately 200 fraudulent transactions processed before detection."
affected_assets: ["fraud detection model", "transaction processing system", "customer accounts"]
detection_method: "automated"
data_breach: false
ai_system_involved: true
Expected output: Severity HIGH (P1), AI incident category: adversarial attack. Immediate response: activate incident plan (A.5.24), contain model, preserve inference logs, assess model integrity. AI-specific controls: A.5.7, A.8.8, A.8.16.
Add to claude_desktop_config.json:
{
"mcpServers": {
"iso-27001-ai": {
"command": "npx",
"args": ["-y", "meok-iso-27001-ai-mcp"]
}
}
}
Or install via Smithery:
npx smithery mcp add nicholastempleman/iso-27001-ai-mcp
Add to .cursor/mcp.json:
{
"mcpServers": {
"iso-27001-ai": {
"command": "npx",
"args": ["-y", "meok-iso-27001-ai-mcp"]
}
}
}
Add to .vscode/mcp.json:
{
"servers": {
"iso-27001-ai": {
"command": "npx",
"args": ["-y", "meok-iso-27001-ai-mcp"]
}
}
}
pip install meok-iso-27001-ai-mcp
| Server | Purpose |
|---|---|
| iso-42001-ai | AI management system — Annex A controls and Annex B risk assessment |
| gdpr-compliance-ai | GDPR DPIA, data subject rights, breach notification |
| eu-ai-act-compliance | EU AI Act risk classification and Annex IV documentation |
| soc2-compliance-ai | SOC 2 Trust Service Criteria and control matrix |
| csoai-governance-crosswalk | 12 compliance frameworks mapped through 52 articles |
MIT © MEOK AI Labs
| Tier | Price | What you get | Stripe |
|---|---|---|---|
| Smoke test | £1 | Signed sample MCP-Hardening report + Article 50 PDF | https://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j |
| Quick Kit | £9 | EU AI Act Article 50 implementation guide (C2PA + EU-Icon) | https://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j |
| Founder Call | £29 | 30-min 1-on-1 with the founder | https://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j |
Refundable. UK Stripe — VAT-clean. Builds on the 81-MCP MEOK fleet. Verify any signed report at https://meok.ai/verify.
Run in your terminal:
claude mcp add iso-27001-ai-mcp -- npx Yes, ISO 27001 AI MCP is free — one-click install via Unyly at no cost.
No, ISO 27001 AI runs without API keys or environment variables.
A hosted option is available: Unyly runs the server in the cloud, no local setup required.
Open ISO 27001 AI on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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