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AIR MCP Server

AIR MCP Server

by VericyIO
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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List open EU AI Act facts

air_list_open_facts
Read-only

Lists open EU AI Act assessment questions that can still change the risk tier, with checklist facts first. Use it to see which facts remain unanswered before finalizing.

Instructions

List the open EU AI Act questions for an assessment: only facts whose answer can still change the tier and that are worth asking now, checklist facts first. screeningGroups are the checklist lines that still hold an open fact. Each item has question (ask it as written), help (one line on why it matters) and, for list facts, options (show the labels, send the values). Boolean facts take true, false, or null for "Not sure"; list facts take option values, or [] for none. answerConflicts are earlier answers that this scan read differently, with the scan's excerpts. Never show factPath, description or a raw null to the person. Prefer air_ask_open_facts when the client can show forms. Requires assessments:read.

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": {
      "assessmentPid": "<assessmentPid>"
    },
    "name": "air_list_open_facts"
  }
}

Input Schema

NameRequiredDescriptionDefault
assessmentPidYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.2

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the readOnly/non-destructive annotations, the description discloses output structure, checklist-first ordering, answer formats for boolean and list facts, how to handle 'Not sure', how to treat answerConflicts, display restrictions, and the required assessments:read scope. This is rich behavioral context that materially helps correct invocation and presentation.

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 purpose is front-loaded and every sentence carries useful information, but the description is dense and packs several distinct concerns into long sentences. It is appropriately sized for a tool with no output schema, though better structuring would improve scanability.

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?

Given the lack of an output schema, the description does the necessary work: it explains screeningGroups, item fields, answer semantics, conflicts, and display restrictions. The only small gap is the implicit assessmentPid definition, which is obvious enough from the parameter name.

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?

There is only one parameter, assessmentPid, but its schema description coverage is 0%. The description implies an assessment context and auth requirement, yet does not explicitly define the parameter or its format; the parameter name is largely self-explanatory, so this is minimally adequate rather than fully compensatory.

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 uses a specific verb and resource ('List the open EU AI Act questions for an assessment') and scopes it to facts that can still change the tier and are worth asking now. It also distinguishes this from the sibling form-based tool air_ask_open_facts, so an agent can tell the two apart without opening either schema.

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?

It explicitly says to prefer air_ask_open_facts when the client can show forms, giving a clear alternative and condition. It does not fully cover when to use this versus other fact-listing siblings, but the primary routing guidance is present.

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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