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Datos.gob.es-MCP

Datos.gob.es-MCP

by AnCode666
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

run_custom_sparql

Execute custom SPARQL queries on over 90,000 datasets from the Spanish Government Open Data Portal. Retrieve specific data by writing valid SPARQL.

Instructions

Run a custom SPARQL query against the datos.gob.es endpoint.

Args: sparql_query: SPARQL query string (must be valid SPARQL)

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": {
      "sparql_query": "<sparql_query>"
    },
    "name": "run_custom_sparql"
  }
}

Input Schema

NameRequiredDescriptionDefault
sparql_queryYes

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 carry the full burden of behavioral disclosure. It only states 'run a custom SPARQL query' without explaining potential impacts like query time, result size, read-only nature, rate limits, or output format. This is insufficient for a powerful query 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 short (two sentences) and front-loaded with the core action. However, the 'Args:' section is informal for MCP. It is concise, but could be more structured (e.g., using standard Markdown).

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 the complexity of custom SPARQL, the lack of output schema, and no annotations, the description is incomplete. It does not mention result format, error handling, or safety considerations, making it harder for an agent to invoke correctly.

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 compensate. It adds that the parameter must be a 'valid SPARQL' string, which is partially helpful but obvious from the parameter name. No further constraints, examples, or format details are provided, leaving the parameter largely under-specified.

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 verb 'Run' and the resource 'custom SPARQL query against the datos.gob.es endpoint'. It distinguishes from sibling tools like get_dataset_details and list_datasets, which are specific retrieval functions. The purpose is unambiguous.

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?

The description provides no guidance on when to use this tool versus its siblings. It does not mention that this tool should be used only when the specific dataset/list tools are insufficient, nor does it note any prerequisites or alternatives.

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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