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FINOS AI Governance MCP Server

FINOS AI Governance MCP Server

Official
by finos
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Get Risk

get_risk

Retrieve complete AI governance risk documents by risk ID to analyze threats, impacts, likelihood, and context for security assessments, compliance audits, and risk planning.

Instructions

Get the complete content of a specific AI governance risk document for detailed threat analysis.

Use this tool to retrieve comprehensive risk information including threat descriptions, impact assessments, likelihood analysis, and contextual details. Essential for security assessments, compliance audits, and risk management planning.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "risk_id": "<risk_id>"
    },
    "name": "get_risk"
  }
}

Input Schema

NameRequiredDescriptionDefault
risk_idYesRisk document identifier from list_risks(), e.g. 10_prompt-injection; the short form the documents use, ri-10 or 10, is accepted too.

Output Schema

NameRequiredDescriptionDefault
titleYes
contentYes
sectionsYes
document_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose that the response is the complete document including threat descriptions, impact and likelihood sections, which usefully sets expectations about payload size and depth. It says nothing about permissions, what happens on an unknown ID, or whether retrieval is read-only — though the verb 'get' and the output schema make the read nature reasonably evident.

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?

Two sentences, front-loaded with the core action and followed by content expectations and use cases. The second sentence is slightly padded with generic audience language ('Essential for...') that adds modest value.

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?

For a single-parameter retrieval tool with a 100%-covered schema and an output schema, the description is sufficient: purpose, contents, and audience are all covered. The only real gap is the discovery path to a risk_id, which the schema's reference to list_risks() already bridges.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents risk_id fully, including accepted short forms and examples. The description adds no parameter-level meaning beyond that, which is the expected baseline when the schema does the work.

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?

The description names a specific verb and resource: fetching the complete content of an AI governance risk document, scoped to 'a specific' one. The resource ('risk document') implicitly separates it from siblings like get_framework or get_mitigation, though no sibling is named explicitly.

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

Usage Guidelines3/5

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

It gives use-case framing (security assessments, compliance audits, risk management planning) but never states when to pick this over list_risks/search_frameworks or that an ID must first be obtained via list_risks(). Usage is implied by scenario, not by explicit routing rules or exclusions.

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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