FINOS AI Governance MCP Server

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List Risks

list_risks

Discovers available AI governance risk documents to support threat assessment, privacy and compliance review, and security planning for AI systems.

Instructions

List all available AI governance risk documents for threat assessment and security planning.

Use this tool to discover security risks, privacy threats, and compliance vulnerabilities in AI systems. Each risk document provides detailed threat analysis, impact assessment, and contextual information for risk management decisions.

Each entry is named and described by the document itself, so this reads every document in the catalog rather than only the file listing -- one cached fetch per document. A document that cannot be read keeps a name derived from its filename and has no description, so the listing is always complete.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_risks"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`source`	Yes
`documents`	Yes
`total_count`	Yes
`document_type`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 11, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations present, the description carries the full behavioral burden and does so substantively: it discloses that the catalog is read document-by-document (one cached fetch per document), which signals latency and cost, and that unreadable documents fall back to filename-derived names with no description so the listing stays complete. What it does not state explicitly is that this is a pure read with no side effects, though "List" strongly implies it.

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

Conciseness4/5

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

The structure is front-loaded and sensible: purpose, then use case, then the operational caveat about per-document fetching. There is mild redundancy between "for threat assessment and security planning" and the later "for risk management decisions," but no sentence is purely filler.

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

Completeness5/5

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

An output schema exists, so return values need not be spelled out, and the description still covers the non-obvious behaviors an agent would otherwise get wrong: per-document fetching, caching, and degraded fallback entries that lack descriptions. For a zero-parameter listing tool, that is complete enough to call correctly and to interpret partial results.

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?

The tool takes zero parameters, so the baseline of 4 applies and there is no parameter meaning for the description to add. Nothing in the description misdescribes the empty input contract.

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

Purpose4/5

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

"List all available AI governance risk documents" gives a specific verb and resource, and the follow-on sentence clarifies that entries include threat analysis and impact assessment. It does not distinguish itself from siblings like list_frameworks or list_mitigations, so an agent must still infer that this returns risks specifically rather than other governance artifacts.

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?

"Use this tool to discover security risks, privacy threats, and compliance vulnerabilities" supplies a clear use case, so the agent knows this is the entry point for risk discovery. It names no exclusions and does not point to get_risk for detail or search_frameworks as a filtered alternative, leaving the when-not side implicit.

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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