Icp Fit Scorer MCP Server

ICP Fit Scorer MCP Server

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.

What it does

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.

Add this to your Claude Desktop config:

{
  "mcpServers": {
    "mamba-icp-scorer": {
      "command": "npx",
      "args": ["-y", "@mambalabsdev/mcp-icp-fit-scorer"],
      "env": {
        "APIFY_TOKEN": "your-apify-token"
      }
    }
  }
}

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

Prerequisites

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

Example prompts

• "Score clay.com against the b2b_saas template and fetch its signals."
• "How well does stripe.com fit an ICP of mid-market fintech companies? Explain the score."
• "Score figma.com with my scoring config and include the per-signal breakdown."
• "Rate openai.com against this ICP description: enterprise AI teams hiring for go-to-market."

Inputs

• company_domain (required): the primary domain of the company to score. Example: clay.com
• company_name (optional): display name of the company.
• template (optional): name of a prebuilt scoring config.
• scoring_config (optional): a JSON object of scoring weights.
• icp_description (optional): plain-English ICP description. Requires llm_api_key.
• 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.

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:

https://apify.com/mambalabs/icp-fit-scorer

Mamba Labs GTM Suite

This is one of six actors in the Mamba Labs GTM Suite, covering hiring signals, tech stack detection, signal aggregation, job board keyword scanning, LinkedIn URL resolution, and ICP scoring. See them all at https://apify.com/mambalabs.

License

MIT

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