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JanProvaznik

Czech Railways (České dráhy) MCP Server

by JanProvaznik

Search Locations

search_locations

Search for train stations and cities in the Czech Railways network to retrieve station codes for planning connections.

Instructions

Search for train stations and cities in the Czech Railways network. Use this to find station codes for connection searches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional location type filter (e.g., "station", "city")
queryYesSearch query (station or city name, e.g., "Praha", "Brno")
Behavior3/5

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

With no annotations provided, the description must carry the burden of behavioral disclosure. It reveals the scope (Czech Railways network) and purpose (find station codes) but lacks details on authentication, rate limits, or response behavior (e.g., fuzzy matching, sorting). The description is adequate but not exhaustive.

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-loaded with the purpose, and contains no unnecessary words. Every sentence adds value, making it highly efficient for an AI agent to parse.

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 simple tool (2 params, no output schema), the description provides enough context for a basic use case. However, it could be more complete by mentioning response format (e.g., list of stations with codes) or behavior on partial matches. Still, it meets the minimum needs.

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 already documents both parameters (query and type). The description adds extra context (e.g., 'Czech Railways network', examples) but does not significantly enhance understanding beyond the schema's own descriptions. Baseline 3 is appropriate.

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 specifies the action ('Search for') and the resources ('train stations and cities') within the Czech Railways network. It distinguishes itself from sibling tools by explicitly stating it finds station codes for connection searches, which is a specific use case different from tools like search_connections.

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 states to use this tool to find station codes for connection searches, giving clear context. However, it does not explicitly mention when not to use it or provide alternatives, leaving some ambiguity about handling cases where the location is not found.

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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