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Dutch-law-mcp

Dutch-law-mcp

by Ansvar-Systems
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

list_sources

Read-only

List authoritative data sources for Dutch law with provenance metadata on coverage, licensing, freshness, and update frequency to verify data origin and availability.

Instructions

List the authoritative data sources backing this server. Returns provenance metadata for each source (wetten.overheid.nl, rechtspraak.nl, EUR-Lex) including coverage, licensing, freshness, and update frequency. Use this tool to verify data origin and understand what data is available. Set include_stats=true to get row counts per table.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_sources"
  }
}

Input Schema

NameRequiredDescriptionDefault
include_statsNoInclude database statistics (row counts per table). Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.2

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds valuable context about the return content (coverage, licensing, freshness, update frequency) and the optional stats behavior, providing transparency about what the tool does beyond the schema.

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 three sentences, front-loaded with the core purpose, and each sentence adds distinct information: what the tool does, what it returns, and how to use the parameter. No waste or redundancy.

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?

The tool is simple (one optional boolean parameter) and the description fully conveys its scope, output, and usage. It mentions the types of metadata returned, which is sufficient given no output schema exists. The description adequately completes the context needed for an agent to decide when to invoke it.

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 coverage is 100% (the only parameter include_stats is fully described). The description repeats the parameter behavior ('Set include_stats=true to get row counts per table') without adding new meaning, so it aligns with the baseline but doesn't go beyond the 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 lists authoritative data sources backing the server, names specific sources (wetten.overheid.nl, rechtspraak.nl, EUR-Lex), and specifies the output (provenance metadata). This distinguishes it from sibling tools like check_data_freshness, which focuses on currency of specific provisions rather than the sources themselves.

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 explicit usage context: 'Use this tool to verify data origin and understand what data is available.' It explains the tool's role in data provenance verification, though it does not explicitly mention when not to use it or name alternative tools for other tasks.

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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