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Schema.gov.it MCP Server

Schema.gov.it MCP Server

Official
by italia
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Explore Catalog

explore_catalog
Read-onlyIdempotent

List named graphs and ontologies available in the Italian government data catalog for a structural overview.

Instructions

List named graphs and ontologies available in the endpoint.

Args: None

Returns:

  • graphs: List of named graphs in the endpoint

  • ontologies: List of owl:Ontology and skos:ConceptScheme resources

When to use this vs X:

  • use this for a quick structural overview of the endpoint

  • use list_ontologies or list_vocabularies when you want richer, more task-oriented views of ontologies or vocabularies

Note: This tool returns TWO lists in one call (named graphs + ontology/vocabulary resources). Both queries run in parallel for performance.

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": "explore_catalog"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds useful context about parallel query execution and the dual-list return, which goes beyond the annotations without contradicting them.

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 well-structured with separate sections for Args, Returns, When to use, and a Note. Each sentence serves a purpose, no fluff, and information is front-loaded.

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 no output schema, the description fully explains the return value (two lists: graphs and ontologies) and adds context about parallel execution. It covers all necessary information for an agent to understand the tool's behavior and output.

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 has no parameters, and the schema coverage is 100% (empty). The description explicitly states 'Args: None', which is clear but slightly redundant. With no parameters, the baseline is 4, and the description adequately conveys the lack of inputs.

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 lists named graphs and ontologies in the endpoint. It uses the specific verb 'list' and identifies the resources, distinguishing it from siblings like list_ontologies and list_vocabularies by emphasizing a quick structural overview.

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

Usage Guidelines5/5

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

Explicit guidance is provided: use this for a quick structural overview, and use list_ontologies or list_vocabularies for richer views. The Note also mentions parallel execution, providing context for performance considerations.

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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