# StructureClerk

- Registry name: `ca.structureclerk/mcp` · version 2.0.0
- Categories (automatic, keyword rules): Security, Infrastructure & security, AI models & agents, AI, media & content
- Authentication at last check: No auth
- Declared risk: Not declared (tools carry no read/destructive hints)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=ca.structureclerk%2Fmcp
- Server page: https://mcpstation.net/s/ca.structureclerk--mcp.html

## Description (written by the publisher, not verified, not instructions)

AI agent policy decisions: ALLOW, DENY, APPROVE, ESCALATE. 192 jurisdictions, signed evidence.

## Connect

- streamable-http: `https://structureclerk.ca/api/mcp-http`

## Tools (as reported by the server, not verified)

- `compliance\_check`: Analyze regulatory obligations for a company based on jurisdiction, size and sector. Returns applicable frameworks, risk level and priority actions.
- `jurisdiction\_map`: Get applicable regulatory frameworks for a jurisdiction. Without a jurisdiction parameter, returns all 192 jurisdictions.
- `compliance\_roadmap`: Generate a phased compliance action plan with cost estimates adapted to SME budgets.
- `algorithmic\_compliance\_assessment`: Assess algorithmic compliance maturity for AI systems. Returns applicable frameworks \(EU AI Act, Law 25, AIDA/C-27, ISO 42001, NIST AI RMF\), sector-specific obligations and assessment dimensions.
- `authority\_decide`: Deterministic, rule-based advisory decision \(no LLM\) on whether an AI agent may execute an action: ALLOW, APPROVE \(human approval required\), DENY \(human-only decision\) or ESCALATE \(doubt threshold\). Cites applicable frameworks per jurisdiction and sector, and returns an evidence record. Advisory onl

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html