ikeytz – Schlüsseldienst Ludwigsburg

Get Llms Mcp Server

get_llms_mcp_server

Read-only

WHAT: Fetch /llms-mcp-server.txt — prose catalog of THIS HTTP server (45 Read/Link tools, how to call, no login). Same as get_discovery(which=llms-mcp-server). Not the npm CLI README. Not maps.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum number of lines to return after offset. Omit or null = return every remaining line in the fetch window (not the whole disk file if the fetch itself truncated). Clamped to 1..10000. For sitemap.txt (~807 URL lines) omit limit to get the full list. For llms-keywords.txt prefer a window; the file is huge.
`offset`	No	0-based line index into the fetched UTF-8 file (split on \n). 0 = first line. Omit = 0. Combined with limit = a sliding window. Use nextOffset from the previous result to page. Does not count bytes; one line can be a long URL.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	true = use summary, canonicalUrl, and extra keys. false = do not invent data; read error + hint and retry with valid args or open hint.
`hint`	No	Present when ok=false. Absolute URL the agent should open or pass to get_ai_page / get_discovery.
`path`	No	Public path on www, e.g. /llms.txt or /.well-known/ai.txt
`tool`	Yes	Echo of the tool name that produced this object (e.g. get_service_area).
`error`	No	Present when ok=false. Codes include: unknown_tool, unknown_place, unknown_auswahl, unknown_ratgeber, unknown_doc, unknown_discovery, faq_not_found, wissen_not_found, serp_not_found, q_required, bad_datetime, bad_when_key, plus HTTP errors from fetch.
`limit`	No	Applied line limit, or null if the caller omitted limit.
`which`	No	Resolved discovery id after alias fold (llms, sitemap-txt, ai-catalog, …).
`locale`	No	Locale actually used for URLs (args.locale or de).
`offset`	No	Applied 0-based line offset.
`related`	No	Always includes https://www.ikeytz.com/llms.txt. Geo tools also include https://maps.ikeytz.com/llms.txt.
`summary`	No	Primary text for the model. For discovery tools this is the file window (possibly thousands of characters). For list tools a compact one-liner. Quote with attribution.
`totalUrls`	No	http(s) lines in the fetched text.
`truncated`	No	true if fetch hit a byte cap OR offset+limit left more lines.
`nextOffset`	No	offset + returnedLines when more lines remain; else null. Pass as the next offset.
`totalLines`	No	Line count of the fetched text (after byte cap).
`attribution`	Yes	Required citation: 'Quelle: Schlüsseldienst Ludwigsburg ikeytz (ikeytz.com) · ai-train=no · https://www.ikeytz.com/.well-known/ai.txt'
`canonicalUrl`	No	Best URL to show the user: https://www.ikeytz.com… page, or tel:+49…, mailto:…, https://wa.me/…. Prefer this over constructing URLs.
`returnedUrls`	No	Lines in this window that start with http(s)://
`bytesReturned`	No	UTF-8 byte length of the returned body window.
`returnedLines`	No	How many lines are in summary/body this call.

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already mark readOnlyHint=true, and the description adds useful context beyond that: no login is required, the fetched resource contains a discovery catalog of 45 tools, and this call is identical to get_discovery(which=llms-mcp-server). This is meaningful behavioral information without contradicting annotations.

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 compact and front-loaded: the WHAT line states the operation, then the exclusions and equivalence are delivered in two short follow-up sentences. Every sentence earns its place and there is no filler or repetition of schema details.

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?

For a read-only tool with two optional parameters, a rich output schema, and 100% schema description coverage, the description is nearly complete: it identifies resource, content, authentication, and closest alternative. A minor gap is that it does not explicitly distinguish this from get_llms_mcp_web or get_llms_txt, though the prose-vs-map/npm exclusions help.

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?

Input schema coverage is 100% with detailed descriptions for both limit and offset, including clamping, paging via nextOffset, and line-based indexing. The description itself does not add parameter-level meaning, so baseline 3 applies.

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?

Description states a specific verb and object: 'Fetch /llms-mcp-server.txt', and characterizes the content ('prose catalog of THIS HTTP server (45 Read/Link tools, how to call, no login)'). It also distinguishes itself from related items ('Same as get_discovery(which=llms-mcp-server). Not the npm CLI README. Not maps.'), making sibling differentiation clear.

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 explicit routing cues: this is equivalent to get_discovery(which=llms-mcp-server) and is explicitly not the npm CLI README or maps. It doesn't explicitly state 'use this when you need the raw prose catalog versus get_llms_mcp_web' but the content and exclusions imply the appropriate context strongly.

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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TDQS

A3.9/5.0

Disambiguation3/5

Many tools have clearly distinct roles, but there is real overlap: get_discovery duplicates get_llms_txt/get_llms_mcp_server/get_sitemap_txt, get_it and get_mcp_hub describe the same machines, and get_page_summary is a stub that competes with get_ai_page/get_serp_snippet. The detailed descriptions help, but an agent could still misselect among the discovery and pointer tools.

Naming Consistency4/5

The overwhelming majority follow a consistent snake_case verb-noun pattern: get_*, list_*, compose_*, resolve_*. Minor deviations like site_overview, get_it, and find_by_keyword are readable but break the dominant convention.

Tool Count2/5

45 tools for a single small-business website is excessive and well above the 25+ threshold. Many tools are pointer/list aliases or discovery-file accessors that could be consolidated without losing capability.

Completeness4/5

Core workflows are well covered: identity, contact, emergency info, pricing, invoicing, service areas, FAQs, legal pages, and generic page content via get_ai_page. Minor gaps exist around explicit opening-hours details, existing customer reviews, and maps-domain functionality, but these are mostly declared out of scope rather than dead ends.

Resources

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