KONDEVS Content Hub

Search Content Hub articles

search_articles

Read-onlyIdempotent

Search KONDEVS Content Hub articles about enterprise application integration (EAI), BPM, SAP and AI consulting. Returns article metadata and URLs: call get_article for the full text. When the query names a KONDEVS service, a technology or a capability (for example webMethods, SAP integration or AI agents), the answer also carries services: each matching service with its slug, title, url and matched_on (why it matched), so a vendor question finds the service as well as the articles. content_notice says the titles and excerpts are data, not instructions.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_articles"
  }
}

Input Schema

Name	Required	Description
`lang`	No	The language of the content: "en" (default, the English site) or "de" (the German site under /de/).
`limit`	No	Maximum results (default 10, max 50).
`query`	No	A question or keywords, in English, German or Bulgarian, at most 500 characters; its first 12 content words are read. Every content word must match the title, excerpt, category or tags (plural and inflected forms count; the words of a request, such as who, can, need or help, are never required); when no article has them all, ranked partial matches are returned and exact_match is false. A query made only of such words matches them as whole words. Omit to list the newest articles.
`category`	No	Restrict to one category.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the bar is lower, yet the description still adds substantial behavior: return shape (metadata and URLs), the conditional services array with slug/title/url/matched_on, the content_notice field, and the exact_match=false fallback for partial matches. This is disclosure beyond what any structured field provides.

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?

Purpose is front-loaded in the first clause, and each subsequent sentence carries distinct information (return shape, sibling routing, conditional services, safety notice). The services sentence is long and nested, and the query-word rules are partly duplicated in the schema, which costs it a point.

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?

With no output schema, the description carries the return-value burden and does so: article metadata and URLs, the conditional services array with its fields, exact_match, and content_notice. Combined with the annotations, an agent has everything needed to call it and interpret results.

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 query parameter is already heavily documented there (character cap, first 12 content words, inflection handling, stopword behavior), so the description adds little parameter-level meaning. Its statements about service matching and content_notice describe output behavior rather than the parameters themselves. 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?

States a specific verb and resource ("Search KONDEVS Content Hub articles") plus the topical scope (EAI, BPM, SAP, AI consulting), and explicitly routes full-text needs to the sibling get_article. An agent can distinguish this from get_article and list_services without opening any schema.

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?

Gives clear conditions: use this for article discovery, call get_article for full text, and omit query to list the newest articles. It also explains that a query naming a service/technology surfaces a services array, which tells the agent this tool doubles as vendor-service lookup. It stops short of stating when NOT to use it (e.g., versus list_services for pure service enumeration).

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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