Gtm Signals Aggregator MCP Server

GTM Signals Aggregator MCP Server

An MCP server that rolls a company's go-to-market signals into one composite score. It wraps the Mamba Labs GTM Signals Aggregator actor on Apify and returns a Clay-ready flat JSON row to any MCP client.

What's Inside

• What it does
• Quick start
• Prerequisites
• Example prompts
• Inputs
• Output
• Example output
• Features
• Full actor documentation
• Mamba Labs GTM Suite
• License

What it does

Give it a company domain and it runs hiring-signal and tech-stack detection together, then returns a single composite GTM score, a recommended action, and an optional plain-English summary. One call, one row, ready to drop into Clay, a CRM, or an AI agent workflow. All of the analysis runs on Apify. This package is a thin client that calls the actor and hands back the result.

Quick start

You need Node.js 18 or newer and an Apify account with an API token.

Add this to your Claude Desktop config:

{
  "mcpServers": {
    "mamba-gtm-signals": {
      "command": "npx",
      "args": ["-y", "@mambalabsdev/mcp-gtm-signals-aggregator"],
      "env": {
        "APIFY_TOKEN": "your-apify-token"
      }
    }
  }
}

Get your token at https://console.apify.com/account/integrations, paste it in, and restart Claude Desktop. The aggregate_gtm_signals tool will be available.

Prerequisites

• Node.js 18 or newer
• An Apify account with an API token

Example prompts

• "Give me the overall GTM signal score for stripe.com."
• "How strong a GTM target is openai.com? Aggregate their signals."
• "Score figma.com on hiring and tech stack, and explain why."
• "Pull the composite GTM signal for datadoghq.com with a summary."

Inputs

• company_domain (required): the bare company domain, no https:// and no trailing slash. Example: stripe.com
• sources (optional): which signals to aggregate: hiring, tech_stack, funding, events, workplace. Default ["hiring", "tech_stack"]. Each extra source is one more sub actor run on your own Apify account. The composite score is normalized over the sources you selected.
• include_summary (optional): include a plain-English gtm_signal_summary in the output.
• explain_mode (optional): if true, the summary becomes a longer, more detailed explanation.

Output

The tool returns the actor's flat JSON row for the scanned company, including the composite GTM score, a recommended action, the underlying hiring and tech-stack signals, and an optional summary. See the Apify Store page for the full output schema.

Example output

{
  "company_domain": "notion.so",
  "composite_signal": "strong",
  "composite_score": 82,
  "recommended_action": "prioritize",
  "gtm_hiring_signal": true,
  "signal_strength": "high",
  "gtm_role_count": 9,
  "crm_detected": "salesforce",
  "tech_stack_signal": "high",
  "gtm_tool_count": 5,
  "run_date": "2026-05-28"
}

Features

• Combines hiring signals and tech stack detection in a single call
• Flat row with composite_score, composite_signal, and recommended_action
• Optional plain-English gtm_signal_summary
• Designed for AI agent consumption

Full actor documentation

This server is a thin client and holds no analysis logic. For the complete input and output reference, pricing, and run history, see the Apify Store page:

https://apify.com/mambalabs/b2b-buying-signals-hiring-tech-stack-intent-for-clay

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Mamba Labs GTM Suite

This server is part of the Mamba Labs GTM Suite, a fleet of twelve specialized MCP servers for go-to-market signal intelligence, each backed by a dedicated Apify actor.

Built by Mamba Labs | npm | Apify Store

License

MIT

Built by Mamba Labs. https://apify.com/mambalabs