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Datos.gob.es-MCP

Datos.gob.es-MCP

by AnCode666
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_dataset_details

Retrieve comprehensive metadata and properties for any dataset from the Spanish Open Data Portal by providing its unique URI.

Instructions

Get detailed information about a specific dataset.

Args: dataset_uri: URI of the dataset to get details for

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": {
      "dataset_uri": "<dataset_uri>"
    },
    "name": "get_dataset_details"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataset_uriYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the tool 'gets' information, implying a read operation, but discloses no behavioral traits such as idempotency, cost, or authentication needs. The lack of detail is a significant gap for a simple retrieval tool.

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 description is very concise with two short lines and no wasted words. However, it could be slightly more informative without losing conciseness, such as hinting at the return structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, no annotations, and a single parameter with minimal description, the description is incomplete. It does not explain what 'detailed information' includes, leaving agents uncertain about the tool's output and behavior.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must add meaning. It states 'URI of the dataset to get details for', which provides basic context beyond the property name but lacks format, examples, or constraints. This is minimally helpful.

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 clearly states the tool retrieves detailed information about a specific dataset, using 'Get detailed information' as a specific verb+resource. It distinguishes from siblings like get_dataset_distributions or get_datasets_by_theme, which focus on different aspects.

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?

The description implies usage when the agent has a dataset URI and needs details, but it provides no explicit guidance on when to use this tool over alternatives (e.g., get_dataset_distributions) or any exclusions or prerequisites.

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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