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Schema.gov.it MCP Server

Schema.gov.it MCP Server

Official
by italia
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

List Datasets

list_datasets
Read-onlyIdempotent

Retrieve DCAT-AP_IT datasets from the Italian government catalog, including ontologies and vocabularies, with pagination support.

Instructions

List available Datasets (dcatapit:Dataset) in the catalog.

Use this when you explicitly need DCAT-AP_IT dataset records. On schema.gov.it, these are often semantic assets such as ontologies, controlled vocabularies, and related distributions rather than classic tabular datasets, so ontology/vocabulary/SPARQL tools are usually a better starting point.

Args:

  • limit: Maximum datasets per page (default: 20)

  • offset: Number of datasets to skip (default: 0)

Returns:

  • items: List of datasets with labels

  • pagination: Metadata with count, offset, has_more, next_offset

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_datasets"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
offsetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, covering safety and idempotency. The description adds context that the datasets are often semantic assets like ontologies and controlled vocabularies, which is a behavioral trait beyond annotations. It does not contradict 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 concise and well-structured: a brief purpose statement, usage guidance, then clearly labeled Args and Returns sections. Every sentence serves a purpose, and the most important information (what the tool does) comes first.

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 tool is a simple list with 2 parameters, no output schema, and rich annotations, the description covers everything needed: it explains what the tool returns (items with labels and pagination metadata), how to use parameters, and even gives usage context. Nothing is missing for an agent to invoke it correctly.

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

Parameters5/5

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

The input schema has 2 parameters (limit, offset) with no descriptions in the schema (0% coverage). The description compensates fully by providing explicit descriptions: 'Maximum datasets per page (default: 20)' and 'Number of datasets to skip (default: 0).' This adds significant meaning beyond the schema.

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 'List available Datasets (dcatapit:Dataset) in the catalog.' It uses a specific verb ('List') and resource ('Datasets'), and distinguishes itself from siblings by noting that other tools (ontology/vocabulary/SPARQL) are usually better starting points, aligning with the context of the sibling tools list.

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?

The description explicitly says 'Use this when you explicitly need DCAT-AP_IT dataset records.' It also provides guidance on when not to use it: 'so ontology/vocabulary/SPARQL tools are usually a better starting point.' This helps the agent decide between this tool and its numerous siblings.

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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