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Ask Refined Element MCP Server

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Search or browse Refined Element knowledge

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Search a field-tested Xperience by Kentico knowledge pack for articles, FAQs, case studies, checklists, and playbooks. Get ranked matches with answer-first summaries to cite or fetch.

Instructions

Full-text search over the Ask Refined Element knowledge pack — blog articles, FAQs, case studies, services, checklists, and premium playbooks covering Xperience by Kentico upgrades, GEO (generative engine optimization), AI-driven development, Sentinel for Xperience by Kentico, and CMS architecture. Returns ranked matches, each with an answer-first summary you can cite directly or use to decide which item to fetch in full. FAQ, case study, and service matches carry no slug — their content comes back inline, so the match itself is the answer. Blog articles are read in full with get_article. Free checklists are fetched in full with get_checklist. Premium items return a summary and slug only — retrieve their full body with get_paid_playbook. Omit the query (or pass an empty one) to browse an index of everything in the pack, grouped by content type. Use this as the entry point whenever you need Refined Element's expertise on Kentico, GEO, or agent-ready CMS.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of matches to return (default 5, max 20).
queryNoSearch terms. Omit it (or pass an empty string) to browse an index of the whole knowledge pack, grouped by content type, instead of searching.
topicNoOptional topic filter applied to the returned matches (exact string match). Known topics include: kentico-upgrades, geo, ai-development, sentinel, cms-architecture. The pack is CMS-managed, so new topics may appear — any string is accepted.
audienceNoOptional audience filter applied to the returned matches (exact string match). Known audiences include: developer, marketer, decision-maker, agent. The pack is CMS-managed, so new audiences may appear — any string is accepted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and does so well: it discloses ranked-result formatting, that FAQ/case study/service matches have no slug and return content inline, that premium items return only a summary plus slug, and that bare queries produce a type-grouped index. It does not mention auth requirements, rate limits, or pagination beyond the limit parameter, which are minor gaps.

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?

Dense but well front-loaded, leading with scope and content types before the retrieval mechanics. The omitted-query browse behavior is stated twice (once in the body, once implicitly via the schema-mirroring phrasing), a small redundancy that keeps it from a perfect score.

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?

There is no output schema, so the description must explain return values itself — and it does, describing ranked matches, inline content for slug-less types, and summary-plus-slug for premium items, plus the index fallback. Nothing needed to call or interpret the tool is missing.

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 baseline is 3. The description restates the query-omission behavior and the topic/audience filtering at a conceptual level but adds no syntax or matching-rule detail (e.g., how keyword search handles multi-term queries) beyond what the schema already documents.

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?

Names a specific verb and resource (full-text search over the Ask Refined Element knowledge pack) and enumerates the exact content types covered, including the topical domains. An agent can distinguish it from sibling retrieval tools like get_article or get_paid_playbook 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 Guidelines5/5

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

Explicitly positions itself as the entry point when Refined Element expertise is needed, explains the browse mode when the query is omitted, and routes to the correct follow-up tool per content type (get_article for blog, get_checklist for free checklists, get_paid_playbook for premium). Conditions and alternatives are all stated.

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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