CarRentalList

Search CarRentalList

search

Read-onlyIdempotent

Search the whole CarRentalList catalog with one query: rental companies, car model families (Lamborghini Huracán, Rolls-Royce Cullinan…), cities and news articles. Returns ids to pass to fetch, with titles and carrentallist.com urls. Use this when a client only offers search and fetch (ChatGPT connectors, deep research), or to find an entity by name before fetching it. For filtered car lists (price, state, class) search_vehicles is better. No match returns an empty results list.

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": {
      "query": "<query>"
    },
    "name": "search"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	what to look for: a company, a car (make/model), a city, or a news topic ('Lamborghini Huracan Miami', 'Diamond Exotic Rentals')

Output Schema

Name	Required	Description
`as_of`	Yes	date (YYYY-MM-DD) of the catalog's last content change
`results`	Yes
`provenance`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

A4.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered structurally. The description adds the useful edge-case behavior that a no-match query returns an empty results list, plus that results are ids for fetch. That is real added context, but return-shape details are largely redundant given the output schema exists.

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?

Front-loaded with the verb and scope, then usage, then the alternative, then the empty-result edge case. Dense and largely waste-free, though the inline example list ('Lamborghini Huracán, Rolls-Royce Cullinan…') adds length that the schema examples already duplicate.

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 single-parameter search tool with an output schema and full annotation coverage, the description covers scope, usage, alternatives, return pass-through to fetch, and the empty-result case. An agent has everything needed to select and invoke it correctly.

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% and the single parameter's schema description already supplies example queries. The description repeats similar examples (company, car, city, news topic), adding reassurance but no syntax or semantics beyond what the schema states. Baseline 3 is correct when the schema carries the parameter burden.

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?

States a specific verb (search) and resource scope (the whole CarRentalList catalog), then enumerates what is searchable: companies, car model families, cities, news articles. It explicitly distinguishes itself from the nearest sibling, search_vehicles, by naming it for filtered car lists.

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

Usage Guidelines5/5

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

Gives two concrete when-to-use conditions (clients that offer only search+fetch, e.g. ChatGPT connectors/deep research; finding an entity by name before fetching) and an explicit when-not/alternative rule routing filtered car lists to search_vehicles. Nothing is left to inference.

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

All CarRentalList tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?