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Regulatory intelligence for AI agents across jurisdictions
Regulatory intelligence for AI agents across jurisdictions
Remote endpoints: streamable-http: https://ai-compliance-monitor.sgdata.workers.dev/mcp
Valid MCP server (1 strong, 1 medium validity signals). 3 known CVEs in dependencies (1 critical, 2 high severity) Imported from the Official MCP Registry.
4 tools verified · Open access · 3 issues found
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This plugin requests these system permissions. Most are normal for its category.
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-vdineshk-ai-compliance-monitor": {
"url": "https://ai-compliance-monitor.sgdata.workers.dev/mcp"
}
}
}From the project's GitHub README.
Structured regulatory intelligence for AI agents operating across jurisdictions.
The first MCP server purpose-built for AI agent compliance. Check obligations, deadlines, and cross-jurisdiction requirements for the EU AI Act, Singapore IMDA Agentic AI Framework, and Colorado AI Act.
AI agents operating across borders face a fragmented regulatory landscape. The EU AI Act requires automatic logging (Article 12). Singapore's IMDA framework mandates escalation protocols. Colorado demands impact assessments. No existing tool maps agent behavior to specific regulatory requirements across jurisdictions.
This server provides machine-readable, structured regulatory intelligence that AI agents can query at runtime to understand their compliance obligations.
| Tool | Description |
|---|---|
check_obligations | Given an agent use case + jurisdiction → applicable requirements |
get_regulation_articles | Structured regulation details with evidence requirements |
check_deadline | Enforcement dates, penalties, compliance milestones |
compare_jurisdictions | Side-by-side obligation comparison across regulations |
Server URL: https://ai-compliance-monitor.sgdata.workers.dev/mcp
# Check obligations for a hiring agent
curl "https://ai-compliance-monitor.sgdata.workers.dev/api/obligations?use_case=hiring_screening"
# Get EU AI Act requirements
curl "https://ai-compliance-monitor.sgdata.workers.dev/api/regulations?regulation_id=eu-ai-act"
# Check upcoming deadlines
curl "https://ai-compliance-monitor.sgdata.workers.dev/api/deadlines"
# Compare transparency requirements across jurisdictions
curl "https://ai-compliance-monitor.sgdata.workers.dev/api/compare?category=transparency"
# Service stats
curl "https://ai-compliance-monitor.sgdata.workers.dev/api/stats"
| Regulation | Jurisdiction | Status | Key Deadline |
|---|---|---|---|
| EU AI Act | European Union | Active | Aug 2, 2026 (high-risk) |
| IMDA Agentic AI Framework | Singapore | Active (voluntary) | Published Jan 2026 |
| Colorado AI Act (SB 24-205) | Colorado, US | Active | Feb 1, 2026 (enforced) |
npm install -g wrangler)CLOUDFLARE_API_TOKEN and CLOUDFLARE_ACCOUNT_ID environment variables# Clone the repo
git clone https://github.com/vdineshk/ai-compliance-monitor.git
cd ai-compliance-monitor
# Install dependencies
npm install
# Create D1 database
npx wrangler d1 create ai-compliance-monitor-db
# Copy the database_id from output into wrangler.toml
# Run migrations
npx wrangler d1 migrations apply ai-compliance-monitor-db --remote
# Seed regulatory data
npx wrangler d1 execute ai-compliance-monitor-db --remote --file=./migrations/0002_seed_data.sql
# Deploy
npx wrangler deploy
npx wrangler deploy --dry-run
This server feeds behavioral interaction data to the Dominion Observatory, the trust scoring layer for the AI agent economy.
MIT
Built by @vdineshk | Singapore
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