Kódvéna

Schema.org JSON-LD készítése

generate_schema_org

Read-onlyIdempotent

Weboldalba illeszthető Schema.org JSON-LD () a megadott adatokból: LocalBusiness (subtype pl. HairSalon, Dentist, AutoRepair), Restaurant, Organization, Product, FAQPage, Event, BreadcrumbList, WebSite – a Google kiemelt találatainak kötelező mezőivel ellenőrizve. Adatot ne találj ki; ami hiányzik, azt a válasz jelzi.

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": {
      "type": "<type>"
    },
    "name": "generate_schema_org"
  }
}

Input Schema

Name	Required	Description
`sku`	No	Cikkszám
`url`	No	Weboldal / oldal címe
`city`	No	Település
`logo`	No	Logó címe
`name`	No	Név
`type`	Yes
`brand`	No	Márka
`email`	No	E-mail
`image`	No	Kép címe
`items`	No	Morzsamenü szintjei felülről
`price`	No	Ár (csak szám, tizedesponttal)
`country`	No	Országkód, pl. HU
`cuisine`	No	Konyha (étteremnél, vesszővel)
`same_as`	No	Közösségi profilok címei
`subtype`	No	LocalBusiness altípusa (schema.org típusnév), pl. HairSalon
`currency`	No	Pénznem, pl. HUF
`end_date`	No	Esemény vége
`menu_url`	No	Étlap címe
`questions`	No
`telephone`	No	Telefon
`search_url`	No	Belső kereső címe {search_term_string} helyőrzővel (WebSite)
`start_date`	No	Esemény kezdete (ÉÉÉÉ-HH-NNTÓÓ:PP+01:00)
`description`	No	Leírás
`postal_code`	No	Irányítószám
`price_range`	No	Árszint
`availability`	No	Elérhetőség, pl. InStock
`location_name`	No	Helyszín neve
`opening_hours`	No
`street_address`	No	Utca, házszám

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A3.9/5.0

Behavior4/5

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

The annotations already establish that this is a read-only, idempotent, non-destructive operation. The description adds meaningful behavioral context: it validates output against Google required fields, forbids inventing data, and says missing data is reported in the response.

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?

Two sentences, both carrying useful information. The output format and supported types are front-loaded, and the no-invention/missing-data rule is stated compactly without filler.

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

Completeness3/5

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

For a 29-parameter tool with no output schema, the description covers supported types and missing-field reporting but does not explain which parameters are required or relevant for each type. That gap matters because the agent must choose among many type-specific fields.

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 90%, so the schema already carries most parameter meaning. The description repeats the type list and subtype examples but does not clarify which parameters apply to which schema type or explain conditional requirements.

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 that it generates embeddable Schema.org JSON-LD from provided data. It lists the supported schema types and notes validation against Google rich-results required fields, so the tool's purpose is immediately distinguishable from generic SEO tools.

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

Usage Guidelines3/5

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

Usage is implied: create JSON-LD for one of the listed schema types to embed on a website. However, there is no explicit when-to-use or when-not guidance, and it does not contrast itself with nearby siblings such as generate_meta_tags or generate_sitemap.

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

All Kódvéna 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?