Scores a company against your ICP with weighted signals. Returns score, tier, and breakdown.
ICP Fit Scorer MCP Server
The com.mambabuilt/mcp-icp-fit-scorer MCP server scores a company against a user-defined ICP using weighted signals. It returns a computed score, an assigned tier, and a breakdown of the contributing factors.
🛠️ Key Features
Scores company-to-ICP fit using weighted signals
Returns: score, tier, and breakdown
🚀 Use Cases
Evaluating how well a company matches an ICP
Producing tiered ICP fit results with supporting breakdown detail
⚡ Developer Benefits
Structured output (score, tier, breakdown) for downstream logic
Encapsulates ICP-fit computation behind an MCP server interface
⚠️ Limitations
Public source data provided includes description and readme excerpt only; tool names, input parameters, and tool count are not included here.
An MCP server that scores a company against your ideal customer profile. It wraps the Mamba Labs ICP Fit Scorer actor on Apify and returns a Clay-ready flat JSON row to any MCP client.
Give it a company domain and a definition of your ICP, and it scores the company on weighted signals, returning a 0 to 100 score, an A to D tier, and a per-signal breakdown. Define your ICP three ways: a prebuilt template, a JSON scoring config, or a plain-English description (which uses your own LLM key). Turn on fetch_signals and the actor will gather hiring and tech-stack signals for you before scoring. One flat row, ready for Clay, a CRM, or an AI agent workflow. All of the scoring 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.
llm_api_key (optional): your OpenAI or Anthropic key, used only with icp_description.
llm_provider (optional): openai or anthropic.
fetch_signals (optional): let the actor gather hiring and tech-stack signals automatically.
include_explanation (optional): add a score_explanation string to the output.
Define your ICP with exactly one of template, scoring_config, or icp_description.
This server exposes the single-company scoring path. The actor also supports batch inputs (a dataset or CSV of companies) and a results webhook. For those, run the actor directly on Apify.
Output
The tool returns the actor's flat JSON row for the scored company, including icp_score (0 to 100), icp_tier (A to D), the per-signal breakdown, and an optional explanation. See the Apify Store page for the full output schema.
User-defined JSON scoring config with custom weights
Returns icp_score (0 to 100), icp_tier (A to D), and lead_tag
Per-signal point breakdown: hiring, tech stack, headcount, funding, industry
Replaces 6+ manual formula columns in Clay
Full actor documentation
This server is a thin client and holds no scoring logic. For the complete input and output reference, pricing, and run history, see the Apify Store page:
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.