
GTM Signals Aggregator
from mambalabsdev
Rolls hiring and tech-stack signals into a single go-to-market fit score for fast account prioritization. Part of the Mamba Labs signal toolkit.
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.
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, nohttps://and no trailing slash. Example:stripe.cominclude_summary(optional): include a plain-Englishgtm_signal_summaryin 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
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.
| Actor | Immutable Actor ID |
|---|---|
| GTM Hiring Signal Scraper | D7O1SA2EqwHGsGr1P |
| GTM Tech Stack Signal Enrichment | qyd7nNyqFPelQViBx |
| GTM Signals Aggregator | xKdRfnfFNkdMpFuNs |
| Job Board Keyword Signal Scanner | 4DvqpvhMR74NLcDDY |
| Domain to LinkedIn URL Resolver | 3HtnSaqPHOg1Qg5gx |
| ICP Fit Scorer | W161DT8W4kW55dMFh |
| Domain Deliverability Checker | 0tVgxI7A6o9jMlxmc |
| Company Firmographic Enricher | YlUtLWjfPpqykmB8g |
| Company Social Presence Mapper | 4k6CCemkgBDz18m2h |
| Company Identity Resolver | lr8fTRAmZCBZmuwwh |
| Company Change-Event Feed | oX44rS0fkEJ3rXLWe |
| Funding & Press Signal Scanner | FS13X6dhQVgX3XOM6 |
Built by Mamba Labs | npm | Apify Store
License
MIT
Built by Mamba Labs. https://apify.com/mambalabs
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
No common issues documented yet. If you hit a problem, the repository's GitHub Issues page is the best place to look.