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HelloGrowth CRM MCP

@MeruLocal

关于 HelloGrowth CRM MCP

HelloGrowth CRM MCP is an AI-powered CRM integration platform that enables secure AI access to CRM data, lead and customer management, deal tracking, task automation, and business workflow orchestration through a standardized MCP interface.

基本信息

分类

数据与分析

传输方式

stdio

发布者

MeruLocal

提交者

SEO Meru Fintech

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "hellogrowthcrm": {
      "url": "https://mcp.hellogrowthcrm.com/sse"
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is HelloGrowth CRM MCP?

It is a Model Context Protocol (MCP) server that discovers, identifies, and governs bots interacting with a website. It also exposes the entire HelloGrowth CRM website as MCP tools, allowing any MCP-capable client (e.g., Claude Desktop, Cursor) to query bot traffic and access website content.

How to use HelloGrowth CRM MCP?

Clone the repository, copy .env.example to .env, run npm install && npm run build, then start with node dist/index.js (or npm run dev for development). The server communicates over stdio; configure it as an MCP server in your client using the path to dist/index.js and environment variables such as DEFAULT_TARGET_URL.

Key features of HelloGrowth CRM MCP

  • Eight bot governance tools for full lifecycle management
  • 55+ known bot signatures with risk scoring
  • Behavioural risk scoring from 0 to 100
  • PTR + forward DNS identity verification
  • robots.txt and sitemap.xml parser with proper semantics
  • 73 additional website data tools (blog, pricing, features, etc.)

Use cases of HelloGrowth CRM MCP

  • Scan your live site for all bots and their risk levels
  • Analyze access logs to get per-bot summaries with risk scores
  • Generate a policy-driven robots.txt file that blocks AI crawlers
  • Look up a specific bot’s identity using IP and User-Agent
  • Query HelloGrowth CRM website content (blog, help, pricing) via natural language

FAQ from HelloGrowth CRM MCP

How does bot detection work?

It uses User-Agent matching against a curated database, plus generic heuristics for unknown bots, and behavioural enrichment from access logs.

What are the runtime requirements?

Node.js, npm, and TypeScript. The server runs as a stdio process; no database or external service is required for bot governance

评论

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