MCP server for content creators — trend analysis, blog research, translation, and free images in one place
Server has 7 tools with basic schemas and descriptions, but significant gaps limit production readiness. All tools have input schemas with type definitions and descriptions present, meeting minimum baseline. However, descriptions are often generic (e.g., 'Check which APIs are configured and available' for api_status is only 52 chars, below the 194-char production average). Output schemas are completely undocumented, LLMs cannot predict response structure. No error handling guidance (e.g., 'If Naver API fails, try again in 5 minutes' or 'Check api_status to verify credentials'). Parameter constraints lack specificity: 'max 5' keywords and 'max 20' results are mentioned in descriptions but not enforced via JSON Schema enums/maxItems. No pagination support despite search tools returning lists. Tool composition is reasonable (each does one thing), but research_topic combines 4 APIs into one call, risking cascading failures with no partial-result fallback. Security: API keys are injected via .env (good), but no audit logging or permission gates visible. Naming follows verb_noun convention (search_blogs, translate_text), solid. Missing: output field documentation, error recovery paths, rate-limit guidance, and idempotency markers.
Check which APIs are configured and available.
All-in-one content research: trends + blogs + news + images for a topic. This is the main tool — it combines all APIs into a single research report. - topic: Research topic in Korean (e.g. '인공지능') - english_topic: Same topic in English for image search (e.g. 'artificial intelligence'). If empty, uses the Korean topic.
Search Naver blogs for a topic. Great for finding popular content and angles. - query: Search keyword - count: Number of results (default: 5, max: 20)
Search free-to-use images on Unsplash. - query: Search keyword (English recommended for better results) - count: Number of images (default: 5)
Search latest news articles on Naver. - query: Search keyword - count: Number of results (default: 5, max: 20)
No output schemas documented. LLMs cannot predict response structure (fields, types, nesting). All 7 tools return unstructured markdown strings instead of typed JSON objects.
No error recovery guidance. When Naver API fails (e.g., 'API key invalid'), tools return raw exception strings. LLMs cannot determine if error is retryable, user-fixable, or fatal.
Parameter constraints not enforced in JSON Schema. 'keywords: max 5' and 'count: max 20' are mentioned in descriptions but not declared as maxItems/maximum in schema. LLMs may pass invalid values.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 55 | 2026-07-28+ | v2 |
Translate text using Naver Papago. - text: Text to translate - source: Source language code (en, ko, ja, zh-CN, etc.) - target: Target language code
Analyze Naver search trends for given keywords. - keywords: List of keywords to compare (max 5) - months: How many months back to analyze (default: 6)
research_topic combines 4 APIs (trends, blogs, news, images) into one call. If one API fails, entire report fails with no partial-result fallback. Violates single-responsibility principle.
No pagination support for list-returning tools (search_blogs, search_news, search_images). Results capped at 20 but no offset/limit params or next_cursor. Large result sets will exhaust context.