Skip to main content
Glama

check_jurisdiction

Find the responsible public authority for a German place by climbing its administrative levels and returning the first level with a listed body, including the evidence trail.

Instructions

Which authority covers a given place? GREEN — returns the evidence trail.

Resolves ``/georegion/?name=<place>``, walks its ``part_of`` chain upwards, and asks
``/publicbody/?regions=<id>`` level by level, from the most specific outwards. It
stops at the **first level that yields any authority**, because that is the body
actually responsible; the remaining, wider levels are reported by id only.

This matters in states such as Rhineland-Palatinate, where an *Ortsgemeinde* is often
not listed on fragdenstaat.de at all while the *Verbandsgemeindeverwaltung* that runs
its administration is.

Args:
    place_name: name of the municipality, district or state.
    include_wider: also list the authorities of the wider levels. Off by default —
        at country level that is thousands of bodies and tells you nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
place_nameYes
include_widerNo

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it delivers: it explains the resolution algorithm, the stopping rule ('first level that yields any authority'), why that rule matters, and what happens at wider levels ('reported by id only'). It also discloses the default behavior of include_wider and its rationale, giving substantial behavioral context.

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 compact and front-loaded, moving from purpose to algorithm to example to parameters. Every section earns its place, though the initial 'GREEN —' fragment is cryptic and slightly distracting without explanation. Overall it is efficiently structured with little waste.

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 absence of an output schema and annotations, the description explains the input semantics, the algorithm, the stopping condition, and the nature of the returned evidence trail. It does not specify the exact response structure or edge cases such as unknown places or levels with no authorities, so it is strong but not fully exhaustive.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates: place_name is defined as 'name of the municipality, district or state', and include_wider is explained semantically ('also list the authorities of the wider levels') plus its default and why it defaults to false. This adds real meaning beyond the raw schema titles.

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 opens with the precise question 'Which authority covers a given place?' and then explains the resolution mechanism by walking the georegion and publicbody hierarchy. This clearly identifies a specific verb+resource behavior and distinguishes it from sibling tools like search_authorities or get_authority by focusing on place-to-jurisdiction resolution rather than keyword search or direct lookup.

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 gives a clear use case: determining the responsible authority for a municipality, district, or state, with a concrete Rhineland-Palatinate example. It also explains when include_wider is inappropriate ('at country level that is thousands of bodies'), but it does not explicitly name alternatives or state when not to use this tool versus search_authorities.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/notDIRK/fds-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server