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Datos.gob.es-MCP

Datos.gob.es-MCP

by AnCode666
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_dataset_distributions

Retrieve the distributions (file formats) available for a dataset by providing its URI. Identify accessible file types.

Instructions

Get available distributions (file formats) for a specific dataset.

Args: dataset_uri: URI of the dataset

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_distributions"
  }
}

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 must disclose all behavioral traits. It states only that it retrieves distributions, but does not mention whether it requires authentication, is read-only, handles errors for missing datasets, or any side effects. The description is insufficient for transparency.

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

Conciseness3/5

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

The description is very short and uses a brief sentence plus an Args section. While concise, it lacks structured sections (e.g., Returns, Notes) and the Args formatting is minimal. It is functional but could be better organized.

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?

For a simple tool with no output schema and no annotations, the description is too sparse. It fails to explain what distributions are, how results are returned, possible error conditions, or behavior for invalid URIs. The sibling context provides some differentiation but completeness is lacking.

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?

The single parameter 'dataset_uri' has 0% schema description coverage. The description adds only 'URI of the dataset', which is essentially the same as the schema title. It does not provide format, example, or constraints beyond what the schema already implies.

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 ('Get') and resource ('available distributions (file formats) for a specific dataset'), clearly stating what the tool returns. It distinguishes itself from siblings like 'get_dataset_details' which likely returns metadata, and search tools.

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs alternatives. Siblings are listed but no explicit comparisons, prerequisites, or exclusion criteria are provided.

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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