orbator-mcp

AI visibility checks, software recommendations and tool comparisons from measured AI answer data

사용해야 할까요

품질 및 안전성

A
설명 품질
93%
스키마 완전성
98%
이름 품질
95%
오염 위험
100%
권한 일치
100%
프로토콜 준수
100%

발견 사항 (1)

  • LOWTool 'compare' description lacks action verbcompare에서

도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.

컨텍스트 비용

~730토큰 (도구 정의)
~847 B일반적인 응답 크기
중간 정도의 주의 영향 (128k 컨텍스트의 0.57%)

이는 서버의 도구가 모델의 컨텍스트에 로드될 때마다 소비되는 대략적인 토큰 수입니다. 수치가 높을수록 다른 작업에 사용할 수 있는 주의가 줄어듭니다.

설치

원클릭 설치

`claude_desktop_config.json` 파일에 다음을 추가하세요:

{
  "mcpServers": {
    "orbator-mcp": {
      "url": "https://api.orbator.io/api/mcp"
    }
  }
}

원격 엔드포인트

https://api.orbator.io/api/mcpstreamable-http

할 수 있는 일

도구 목록

도구 (4)

🟢 읽기 전용🟡 쓰기🔴 삭제⚪ 알 수 없음
🟢find_tools(category, constraints, limit)

Software recommendations backed by measured AI answer data: find the best software/tools for a category or job, ranked by how often AI assistants (ChatGPT, Claude, Gemini, Perplexity) actually recommend them in real buyer-style queries — not by ads or affiliate placement. Use when asked "what software/tool should I use for X", "best X tools", or for vendor-neutral software recommendations. Pass the category in plain words (e.g. "uptime monitoring", "CRM for freelancers"); it is fuzzy-matched against published Index categories, and near-miss inputs return suggested categories to retry with. Returns ranked products with recommendation share %, 4-week trend, and per-engine breakdown.

입력 스키마

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "description": "Software category or job to find tools for, in plain words (e.g. \"ci/cd\", \"landing page builders\")."
    },
    "constraints": {
      "type": "string",
      "description": "Optional buyer constraints (e.g. \"open source\", \"free tier\", \"self-hosted\"). Echoed back with the data for the caller to weigh — not yet applied server-side."
    },
    "limit": {
      "type": "number",
      "description": "Max recommendations to return (default 10, max 50)."
    }
  },
  "required": [
    "category"
  ]
}
🟢get_ai_index(category)

AI visibility check — which software AI recommends for a category. Returns the full AI Recommendation Index for one software category: the complete measured ranking of products AI assistants (ChatGPT, Claude, Gemini, Perplexity) recommend, with recommendation share %, average answer position, per-engine breakdown, 4-week trend, sample size, and methodology. Use to answer "does AI recommend <product>" (look up its row and rank), "who is winning AI recommendations in <category>", or to cite AI recommendation-share data. Pass category in plain words or as a slug; omit it (or pass "categories") to list all published categories.

입력 스키마

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "description": "Category in plain words or slug form (e.g. \"uptime monitoring\", \"ci-cd-tools\"). Omit or pass \"categories\" to list every published category with sample sizes."
    }
  }
}
🟢get_facts(product)

Canonical software product facts with sources — pricing, features, integrations, platform, and limits, where every fact carries a source URL and a last-verified date. Use to verify software claims (e.g. current pricing) or to gather grounded data before recommending or comparing tools. Accepts a product name or domain (e.g. "hubspot.com").

입력 스키마

{
  "type": "object",
  "properties": {
    "product": {
      "type": "string",
      "description": "Product name or canonical domain, e.g. \"hubspot.com\"."
    }
  },
  "required": [
    "product"
  ]
}
⚪compare(product_a, product_b)

Compare software/tools side by side — a fact-by-fact comparison of two products (pricing, features, integrations, limits) with source URLs and verified dates for every claim. Use for "X vs Y" software comparison questions. Accepts product names or domains; pair order does not matter.

입력 스키마

{
  "type": "object",
  "properties": {
    "product_a": {
      "type": "string",
      "description": "First product name or domain."
    },
    "product_b": {
      "type": "string",
      "description": "Second product name or domain."
    }
  },
  "required": [
    "product_a",
    "product_b"
  ]
}

권장 프롬프트

search_research
Search for information about [topic] using orbator-mcp
예상 도구: find_tools
find_specific
Find [specific item] using orbator-mcp
예상 도구: find_tools
retrieve_data
Get details about [item] from orbator-mcp
예상 도구: get_ai_index
fetch_info
Fetch [information type] using orbator-mcp
예상 도구: get_ai_index
research_workflow
Search for [topic], then get detailed information about the top results using orbator-mcp
예상 도구: find_toolsget_ai_index

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