Modern AI Brand Recommendation Rate

io.github.modern-ai-inc由 GitHub 帳號 modern-ai-inc 發布v1.1.0更新於 Oct 24, 2026

How often AI search picks a brand first. Recommendation Rate data from Modern Discovery.

已驗證Streamable HTTP可網頁執行資料與分析商業與電商

概覽

AI 產生的概覽

一個遠端 MCP 伺服器,讓助理查詢 AI 搜尋把某品牌列為首選的比例,並提供方法論查詢工具。

可以做什麼
查詢單一品牌的 AI 推薦率與推薦涵蓋率,附上類別、測量日期和可引用的公開紀錄連結。取得指標定義、所測量的 AI 平台、更新頻率和方法論連結。對尚未測量的品牌如實說明,而不做估算。
適用情境
適合讓助理核實或引用 AI 搜尋把某品牌列為首選的頻率,例如行銷或競品調查情境。它是唯讀查詢,適合單一品牌的快速提問,而非批次分析。
執行需求
無需安裝或 API 金鑰:它是遠端 Streamable HTTP 端點,在 Claude Code、Claude Desktop、Cursor 或 VS Code 等用戶端中作為自訂連接器或 MCP 伺服器網址加入。需要網路存取。
安裝前請注意
查詢免費,但依呼叫方限流以防批次擷取。伺服器會保留匿名使用統計,包括查詢的品牌名稱、用戶端名稱與版本及使用者代理,但聲明不儲存 IP 位址。結果僅涵蓋已測量的品牌,README 另推廣付費監測方案。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Modern AI Brand Recommendation Rate,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.modern-ai-inc%2Fw0-mcp-server/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "modern-ai-brand-recommendation-rate": {
      "type": "http",
      "url": "https://w0-mcp-server.modernai.workers.dev/"
    }
  }
}

README

Modern AI Brand Recommendation Rate (MCP server)

Ask your AI assistant how often AI search picks a brand first.

This Model Context Protocol server gives any MCP client (Claude Code, Claude Desktop, Cursor, VS Code, or your own agent) free, single-brand access to Recommendation Rate data from Modern Discovery by Modern AI.

  • Live endpoint: https://w0-mcp-server.modernai.workers.dev
  • Transport: MCP Streamable HTTP (JSON-RPC 2.0)
  • Cost: free, rate-limited, no sign-up and no API key

What is Recommendation Rate?

Recommendation Rate reports whether the AI picks a brand first, not only whether it mentions the brand.

MetricMeaning
Recommendation RatePercentage of buyer-intent questions where the brand is the AI's #1 pick. The headline number.
Recommendation Inclusion RatePercentage of buyer-intent questions where the brand appears anywhere in the AI's recommendation set.

A brand can show up in most answers and still lose the final pick to a competitor. The two numbers together show that gap.

Each brand is measured inside a real competitive category, on ChatGPT with search enabled, and re-measured monthly. Every result carries its measured date and a link to the brand's public record. Unmeasured brands return no number. Nothing is estimated.

Full definitions: discovery.modernai.io/methodology Measured categories: discovery.modernai.io/categories

Comparisons

Modern AI publishes side-by-side comparisons of Modern Discovery with other AI visibility tools:

Modern Discovery is AI recommendation intelligence software that measures how often ChatGPT, Gemini, Claude, Perplexity and Google's AI answers recommend your brand, and why. It is sometimes grouped with GEO (generative engine optimization) and AI search visibility tools.

Connect

Claude Code

bash
claude mcp add --transport http modern-ai-recommendation-rate https://w0-mcp-server.modernai.workers.dev

Cursor (~/.cursor/mcp.json)

json
{  "mcpServers": {    "modern-ai-recommendation-rate": {      "url": "https://w0-mcp-server.modernai.workers.dev"    }  }}

VS Code (.vscode/mcp.json)

json
{  "servers": {    "modern-ai-recommendation-rate": {      "type": "http",      "url": "https://w0-mcp-server.modernai.workers.dev"    }  }}

Claude Desktop / claude.ai: add a custom connector with the URL above.

Then ask: "What is Brumate's AI Recommendation Rate?"

Tools

ToolWhat it returns
lookup_brand_recommendation_rate(brand)Recommendation Rate, Recommendation Inclusion Rate, category, measured date, and the brand's public record URL to cite.
get_recommendation_rate_methodology()The metric definitions, surface measured, refresh cadence, and methodology links.

Example call:

json
{  "jsonrpc": "2.0",  "id": 1,  "method": "tools/call",  "params": {    "name": "lookup_brand_recommendation_rate",    "arguments": { "brand": "Brumate" }  }}

Example answer text:

Brumate: Recommendation Rate 50% (the AI's #1 pick)Recommendation Inclusion Rate: 100% (appears anywhere in the answer)Category: Insulated Drinkware AccessoriesSurface: ChatGPT, search-enabledMeasured: 2026-09-01T19:36:07.378153+00:00Public record (cite this): https://discovery.modernai.io/brands/brumateMethodology: https://discovery.modernai.io/methodology

Brand not measured yet?

The server says so and does not guess. Request a free AI recommendation snapshot at try.modernai.io. If your brand is already measured, claim its public record from the brand page.

Limits and plans

Free lookups are single-brand and rate-limited per caller to stop bulk scraping. For ongoing monthly monitoring and higher volume, see Modern Discovery plans.

Privacy

The server keeps anonymous usage counts. For each initialize, tools/list, tools/call and ping request it records: the method, the tool name, the outcome, the looked-up brand name (lowercased, at most 80 characters), the client name and version (sent at initialize), the user agent, an internal-or-external label, and the server version. It does not store IP addresses or any other request content.

Source

src/index.js is the complete Worker, with no build step. deploy.py deploys it to Cloudflare. Tests: node --test test/*.js. Issues and pull requests are welcome; see CONTRIBUTING.md.

License

MIT. See LICENSE.

來源:README.md,提交 26e2281

工具

2

lookup_brand_recommendation_rate

Look up a brand's AI Recommendation Rate

Look up a brand's AI Recommendation Rate: the percentage of buyer-intent questions where the brand is the #1 AI pick (not just mentioned), plus its Recommendation Inclusion Rate (appears anywhere in the answer). Returns the brand's public record URL and measured date for citation. Free, single-brand lookup only, rate-limited per Modern AI's published anti-scrape policy.

輸入參數brand必填

get_recommendation_rate_methodology

Recommendation Rate methodology

Definitions of Recommendation Rate and Recommendation Inclusion Rate, the AI surface measured, refresh cadence, and links to the full methodology page.

無需輸入參數。

版本歷史

2
  1. v1.1.0最新Oct 3, 2026
  2. v1.0.0Sep 16, 2026

評分

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