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Glama

Data Europa

by io.github.pipeworx-io

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Read-onlyIdempotent

Search the EU open-data portal (data.europa.eu) for datasets by free-text query; supports Solr filter expressions (e.g. country.iso:DE), pagination via rows/start, and sorting. Returns dataset titles, descriptions, and publisher info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fqNoSolr filter (e.g. "country.iso:DE").
rowsNo1-1000 (default 25).
sortNo
queryYes
startNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoTotal number of matching results
resultsNoArray of matching datasets

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "agriculture exports"
+  },
+  {
+    "fq": "country.iso:DE",
+    "query": "employment statistics",
+    "rows": 50
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Search results from data.europa.eu API",
+  "properties": {
+    "count": {
+      "description": "Total number of matching results",
+      "type": "number"
+    },
+    "results": {
+      "description": "Array of matching datasets",
+      "items": {
+        "description": "Dataset metadata",
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral detail: supports Solr filter expressions, pagination via rows/start, sorting, and returns dataset titles, descriptions, and publisher info. No contradiction with 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 two sentences, front-loads the main purpose, and includes a concrete Solr filter example. Every word earns its place, no fluff.

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?

For a search tool with 5 parameters, an output schema, and comprehensive annotations, the description covers all essential invocation aspects: the target portal, query semantics, optional filters, pagination, sorting, and return content. It is sufficient for correct selection and invocation.

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?

Schema description coverage is only 40% (fq and rows have descriptions). The description compensates by explaining the query is free-text, fq is for Solr filters, rows/start enable pagination, and sort is for sorting. This adds meaning beyond the raw 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 the tool: 'Search the EU open-data portal (data.europa.eu) for datasets by free-text query'. It specifies the verb (search), the resource (EU open-data portal), and the scope (datasets), distinguishing it from siblings like search_within by naming a specific external portal.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool (searching EU open-data datasets) and mentions supported capabilities (Solr filters, pagination, sorting). It does not explicitly name alternatives or exclusions, but the specific resource and scope imply the appropriate use case.

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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TDQS

A3.5/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded are highly similar; deep_research also overlaps with ask_pipeworx. This makes it hard for an agent to distinguish which to use.

Naming Consistency2/5

Tool names are inconsistent, mixing camelCase (ask_pipeworx, ai_visibility_check) with snake_case (deep_research, compare_entities). Some are verb phrases, others are nouns (groups, tags), with no unified pattern.

Tool Count2/5

With 36 tools covering EU open data, general data retrieval (Pipeworx), and prediction markets (Polymarket), the count is too high for a coherent, focused server. Many tools are redundant or meta-tools.

Completeness2/5

For a server named 'Data Europa', the EU open-data tools are basic (search, package, groups) lacking update/delete or analysis. The additional Pipeworx/Polymarket tools are extensive but unrelated, making the overall surface incomplete for the implied domain.

Resources