Modern AI Brand Recommendation Rate

io.github.modern-ai-inc由 GitHub 账号 modern-ai-inc 发布v1.1.0更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行数据与分析商业与电商

概览

AI 生成的概览

一个远程 MCP 服务器,让助手查询 AI 搜索把某品牌列为首选的比例,并提供方法论查询工具。

可以做什么
查询单个品牌的 AI 推荐率与推荐包含率,附类别、测量日期和可引用的公开记录链接。获取指标定义、所测量的 AI 平台、更新频率和方法论链接。对尚未测量的品牌如实说明,而不做估算。
适用场景
适合让助手核实或引用 AI 搜索把某品牌列为首选的频率,例如营销或竞品调研场景。它是只读查询,适合单品牌的快速提问,而非批量分析。
运行要求
无需安装或 API 密钥:它是远程 Streamable HTTP 端点,在 Claude Code、Claude Desktop、Cursor 或 VS Code 等客户端中作为自定义连接器或 MCP 服务器地址添加。需要网络访问。
安装前请注意
查询免费,但按调用方限流以防批量抓取。服务器会保留匿名使用统计,包括查询的品牌名、客户端名称与版本及用户代理,但声明不存储 IP 地址。结果仅覆盖已测量的品牌,README 还推广付费监测方案。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Modern AI Brand Recommendation Rate,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.modern-ai-inc%2Fw0-mcp-server/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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.

来源: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.

输入参数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.

无需输入参数。

版本历史

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

评分

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