eu-ai-act-mcp

EU AI Act FAQ

euaiact_answer_question

Read-onlyIdempotent

Get best-match answers to EU AI Act questions with article references on classification, deadlines, roles, governance, documentation, risk, penalties, and more.

Instructions

Search frequently asked questions about the EU AI Act and get best-match answers with article references. Covers classification, deadlines, roles, governance, documentation, risk assessment, penalties, GPAI systemic risk, FRIA, transparency, and sector-specific guidance.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`question`	Yes	User question about the EU AI Act

Output Schema

TableJSON Schema

Name	Required	Description	Default
`answer`	Yes
`question`	Yes
`confidence`	Yes
`lexbeam_url`	No
`matched_question`	No
`article_references`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.5.0Aug 19, 2026
- addedOutput schema / properties / matched_question
```
Added value: +{
+  "type": "string"
+}
```
First observedv1.1.5Jun 14, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations declare readOnly and idempotent, so the bar is lower. The description adds context by claiming 'best-match answers' and 'article references,' which implies ranking behavior and output structure, beyond annotations.

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

Conciseness5/5

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

The description is a single, informative sentence that covers function, scope, and output references without excess. Front-loaded with action and resource.

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 simple schema and annotations, the description covers the purpose, scope, and output (references). It could mention limitations or fallback behavior, but it's sufficiently complete for a Q&A tool.

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?

The schema has one parameter with a clear description ('User question about the EU AI Act'). The tool description adds no additional parameter context, but since the schema coverage is 100%, a 3 is acceptable.

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's purpose: 'Search frequently asked questions about the EU AI Act and get best-match answers with article references.' It uses a specific verb (search) and resource (FAQ) and differentiates from siblings like get_article by focusing on question-answer style.

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 implicitly indicates when to use this tool (for general FAQ-style questions) by enumerating covered topics, but it does not explicitly contrast it with alternatives like checking specific articles or deadlines. The 'Covers...' list provides usage context but lacks explicit when-not guidance.

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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