dutch-gov-mcp

query_cbs_data

Retrieve statistical data from CBS datasets by specifying dataset identifiers, selecting columns, applying filters, and managing result pagination for analysis.

Instructions

Query statistical data from a CBS dataset. Returns observation rows.

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_id": "<dataset_id>"
    },
    "name": "query_cbs_data"
  }
}

Input Schema

Name	Required	Description
`dataset_id`	Yes	CBS dataset identifier (e.g. "83765NED").
`select`	No	Comma-separated columns to include (e.g. "Measure,Value,Perioden").
`filter`	No	OData filter expression (e.g. "Perioden eq '2023JJ00'").
`max_results`	No	Max rows to return (1-10000).
`offset`	No	Skip N rows for pagination.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Apr 16, 2026

TDQS

B3.2/5.0

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 of behavioral disclosure. It mentions the action ('Query') and output ('Returns observation rows'), but lacks details on permissions, rate limits, error handling, or data freshness. For a query tool with no annotation coverage, this leaves significant behavioral gaps.

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 extremely concise and front-loaded: two sentences that directly state the tool's purpose and output. Every word earns its place with zero waste or redundancy.

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

Completeness4/5

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

Given the tool's moderate complexity (5 parameters, 1 required), 100% schema coverage, and presence of an output schema, the description is reasonably complete. The output schema means the description doesn't need to explain return values. However, the lack of usage guidelines and behavioral transparency (with no annotations) prevents a perfect score.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no parameter-specific information beyond what's in the schema. According to guidelines, with high schema coverage, the baseline is 3 even without param info in the description.

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's purpose: 'Query statistical data from a CBS dataset. Returns observation rows.' It specifies the verb ('Query'), resource ('statistical data from a CBS dataset'), and output format ('observation rows'). However, it doesn't explicitly differentiate from siblings like 'search_cbs_datasets' or 'get_cbs_dataset', which likely serve different purposes.

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 alternatives. With multiple sibling tools like 'search_cbs_datasets' and 'get_cbs_dataset', there's no indication of when this query tool is appropriate versus those for searching or retrieving dataset metadata. No context or exclusions are mentioned.

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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