orbator-mcp

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

我該用這個嗎

品質與安全性

A
說明品質
93%
結構描述完整度
98%
命名品質
95%
汙染風險
100%
權限相符程度
100%
協定合規性
100%

發現項目(1)

  • LOWTool 'compare' description lacks action verb在 compare 中

根據工具定義與協定合規性的自動化分析。

上下文成本

~730Token(工具定義)
~847 B典型回應大小
中等的注意力影響(128k 上下文的 0.57%)

這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。

安裝

一鍵安裝

將以下內容加入你的 `claude_desktop_config.json` 檔案:

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

遠端端點

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

它能做什麼

工具清單

工具(4)

🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢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.

輸入結構描述

{
  "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.

輸入結構描述

{
  "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").

輸入結構描述

{
  "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.

輸入結構描述

{
  "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"
  ]
}

建議的提示詞

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

社群

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證據

近期觀測

已驗證未記錄版本4 個工具
已驗證未記錄版本4 個工具