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CSOAI-ORG

ISO 42001 AI MCP

by CSOAI-ORG
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

generate_policy_template

Generate AI policy templates compliant with ISO 42001. Define organization, scope, and policy type to create structured governance documents.

Instructions

Generate AI policy documents per ISO 42001 requirements.

Creates policy templates that satisfy ISO 42001 clause 5.2 (AI policy) and Annex A.2.2 requirements. Includes AI policy statement, roles and responsibilities, objectives, principles, and governance structure.

Args: organization_name: Name of the organization. ai_scope: Description of AI systems and activities in scope. policy_type: Type of policy ('comprehensive', 'brief', 'executive'). caller: Caller identifier for rate limiting. tier: Pricing tier ('free' or 'pro').

Returns: Markdown-formatted policy template with all required elements.

Behavior: This tool generates structured output without modifying external systems. Output is deterministic for identical inputs. No side effects. Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need to assess, audit, or verify compliance requirements. Ideal for gap analysis, readiness checks, and generating compliance documentation.

When NOT to use: Do not use as a substitute for qualified legal counsel. This tool provides technical compliance guidance, not legal advice. Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
organization_nameYes
ai_scopeNo
policy_typeNocomprehensive
callerNoanonymous
tierNofree
api_keyNo

Tool Definition Quality

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully bears the burden and delivers a comprehensive 'Behavioral Transparency' section covering side effects, authentication, rate limits, error handling, idempotency, and data privacy. This exceeds expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is lengthy with some redundancy between 'Behavior' and 'Behavioral Transparency' sections. While structured, it could be more streamlined without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately explains the return type and includes essential behavioral context. It covers parameters, use cases, and constraints, but missing api_key parameter weakens completeness slightly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, requiring compensation. The description's 'Args' section explains 5 of 6 parameters, adding meaning. However, 'api_key' is missing from that section, and default values or enums are not described, leaving a gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates AI policy documents per ISO 42021 requirements, listing specific clauses and components. It distinctively positions itself among siblings like 'assess_ai_risk' and 'audit_management_system' by focusing on policy template generation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'When to use' and 'When NOT to use' sections, providing clear guidance. However, the 'When to use' is somewhat generic and could be interpreted for multiple sibling tools, lacking explicit differentiation or alternative suggestions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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