What can you do with this server?

This MCP server scores a company domain against an ideal customer profile (ICP) and lists available prebuilt scoring templates. * score_icp_fit: score a single company using a prebuilt template, custom JSON scoring_config, or plain-English icp_description (requires llm_api_key). * Return a 0–100 icp_score, A–D icp_tier, per-signal breakdown, optional explanation, and Clay-ready flat JSON. * Optionally fetch hiring/tech-stack signals, set tier thresholds, skip low scores, compare to a previous score, and cap Apify spend. * Accept optional firmographic, social, hiring, funding, CRM, and tech-stack inputs to compute scoring signals. * list_icp_templates: list six prebuilt templates locally, with no Apify run, token, or charge. * Requires APIFY_TOKEN for scoring; each scoring call consumes Apify credits. Supports single-company scoring only; batch/webhook use the Apify actor directly.

Which integrations are available for this server?

Allows using OpenAI's API (e.g., GPT models) to interpret plain-English Ideal Customer Profile descriptions and convert them into scoring configurations.

mcp-icp-fit-scorer

by mambalabsdev

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

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's Inside

Related MCP server: Company Firmographic Enricher MCP Server

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 and list_icp_templates tools 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

Every input the tool accepts, generated from the server's own tool list.

`score_icp_fit`

Input	Type	Required	Description
`company_domain`	string	yes	The primary domain of the company to score. Example: clay.com
`company_name`	string	no	Optional display name of the company.
`template`	one of `full_signal`, `saas_outbound`, `b2b_services`, `fintech`, `smb_local`, `enterprise`	no	Name of a prebuilt scoring config, one of the six the actor ships: full_signal, saas_outbound, b2b_services, fintech, smb_local, enterprise. Alternative to scoring_config or icp_description. Call list_icp_templates to see them.
`scoring_config`	object	no	JSON object of scoring weights. Alternative to template or icp_description.
`icp_description`	string	no	Plain-English description of your target ICP. Requires llm_api_key. Alternative to template or scoring_config.
`llm_api_key`	string	no	Your OpenAI or Anthropic API key. Required only when using icp_description.
`llm_provider`	one of `openai`, `anthropic`	no	LLM provider to use with icp_description: openai or anthropic.
`fetch_signals`	boolean	no	If true, the actor fetches hiring and tech-stack signals for the company automatically before scoring.
`include_explanation`	boolean	no	If true, adds a score_explanation string to the output describing how the score was derived.
`tier_thresholds`	object	no	Optional. Minimum score for each tier as { "tier_a": number, "tier_b": number, "tier_c": number }. Scores at or above tier_a are A, tier_b are B, tier_c are C, else D. Defaults to 80 / 60 / 40.
`funded_within_days`	integer	no	Optional. How recent a funding round must be to count for the recently_funded signal, in days. Defaults to 540 (18 months).
`min_score_to_output`	integer	no	If set, rows scoring below this threshold are skipped from output (not pushed to dataset). Skipped rows are logged only.
`previous_score`	integer	no	Previous ICP score for this company. If provided, output includes score_change and score_trend fields.
`gtm_hiring_signal`	string	no	Whether the company is actively hiring for GTM/sales roles. Accepts a boolean-like string ("true"/"false"). Sent as a string for Clay compatibility and coerced to boolean at runtime.
`gtm_role_count`	string	no	Number of open GTM/sales roles. Scores via the gtm_role_count_strong signal when at or above min_gtm_roles (default 2). Accepts a numeric string (e.g. "8"). Sent as a string for Clay compatibility and coerced to integer at runtime.
`uses_hubspot`	string	no	Whether the company uses HubSpot. Accepts a boolean-like string ("true"/"false"). Sent as a string for Clay compatibility and coerced to boolean at runtime.
`uses_salesforce`	string	no	Whether the company uses Salesforce. Accepts a boolean-like string ("true"/"false"). Sent as a string for Clay compatibility and coerced to boolean at runtime.
`uses_clay`	string	no	Whether the company uses Clay. Accepts a boolean-like string ("true"/"false"). Sent as a string for Clay compatibility and coerced to boolean at runtime.
`crm_detected`	string	no	Whether any CRM was detected. Accepts a boolean-like string ("true"/"false") or any non-empty CRM name (e.g. "Salesforce"). Sent as a string for Clay compatibility and coerced to boolean at runtime. Auto-derived from uses_hubspot/uses_salesforce if not set.
`seq_tool_detected`	string	no	Whether a sales sequencing tool (Outreach, SalesLoft, Apollo, Lemlist) was detected. Accepts a boolean-like string ("true"/"false") or any non-empty tool name (e.g. "Outreach"). Sent as a string for Clay compatibility and coerced to boolean at runtime.
`tech_stack`	string	no	Comma-separated list of technologies. Used to auto-detect CRM/sequencing tools if booleans are not set.
`headcount`	string	no	Current employee headcount. Accepts a numeric string (e.g. "3000"). Sent as a string for Clay compatibility and coerced to integer at runtime.
`headcount_min`	integer	no	Minimum headcount for the headcount_in_range signal.
`headcount_max`	integer	no	Maximum headcount for the headcount_in_range signal.
`headcount_in_range`	boolean	no	Override: whether headcount is in your target range.
`employee_band`	string	no	Firmographic employee band from the Company Firmographic Enricher (Actor ID YlUtLWjfPpqykmB8g), e.g. "201-500". Scores via employee_band_match when it is in target_employee_bands.
`revenue_estimate`	string	no	Estimated annual revenue in dollars from the Company Firmographic Enricher (Actor ID YlUtLWjfPpqykmB8g). Scores via revenue_in_range. Accepts a numeric string (e.g. "50000000"). Coerced to integer at runtime.
`hq_location`	string	no	Headquarters location from the Company Firmographic Enricher (Actor ID YlUtLWjfPpqykmB8g). Carried for reference; not currently scored.
`founded_year`	string	no	Year the company was founded, from the Company Firmographic Enricher (Actor ID YlUtLWjfPpqykmB8g). Carried for reference; not currently scored. Accepts a numeric string (e.g. "2015").
`recently_funded`	boolean	no	Override: whether the company was recently funded (within funded_within_days, default 540).
`last_funding_date`	string	no	ISO date of last funding round (legacy field; latest_funding_date is preferred). Used to auto-detect recently_funded if the boolean is not set.
`latest_funding_date`	string	no	ISO date of the latest funding round (from C1 Funding & Press Signal Scanner when it ships). Drives recently_funded against funded_within_days.
`latest_funding_amount`	string	no	Dollar amount of the latest funding round (from C1 when it ships). Scores via well_funded when at or above min_funding_amount (default 1000000). Accepts a numeric string (e.g. "50000000").
`funding_stage`	string	no	Funding stage (e.g. seed, series_a, series_b, growth). Used to infer recently_funded.
`industry`	string	no	The company's industry (from the Company Firmographic Enricher, Actor ID YlUtLWjfPpqykmB8g).
`industry_match`	boolean	no	Override: whether the company's industry matches your target list.
`target_industries`	string	no	Comma-separated list of target industries for the industry_match signal.
`social_platforms_found`	string	no	Number of official social platforms found, from the Company Social Presence Mapper (Actor ID 4k6CCemkgBDz18m2h). Scores via social_presence when at or above min_social_platforms (default 2). Accepts a numeric string.
`total_followers`	string	no	Total social followers across platforms, from the Company Social Presence Mapper (Actor ID 4k6CCemkgBDz18m2h). Scores via strong_social_following when at or above min_total_followers (default 1000). Accepts a numeric string.
`has_linkedin`	string	no	Whether a company LinkedIn page was found, from the Company Social Presence Mapper (Actor ID 4k6CCemkgBDz18m2h) or the Domain to LinkedIn URL Resolver (Actor ID 3HtnSaqPHOg1Qg5gx). Contributes to social_presence. Accepts a boolean-like string.
`has_twitter`	string	no	Whether a company X/Twitter profile was found, from the Company Social Presence Mapper (Actor ID 4k6CCemkgBDz18m2h). Contributes to social_presence. Accepts a boolean-like string.
`job_count`	string	no	Number of open jobs found, from the Job Board Keyword Signal Scanner (Actor ID 4DvqpvhMR74NLcDDY). Scores via active_hiring_volume when at or above min_job_count (default 3). Accepts a numeric string.
`keyword_match_count`	string	no	Number of target-keyword matches found, from the Job Board Keyword Signal Scanner (Actor ID 4DvqpvhMR74NLcDDY). Scores via keyword_signal_match when at or above min_keyword_matches (default 1). Accepts a numeric string.
`max_charge_usd`	number	no	Optional spending cap for this call, in USD. The actor stops before any charge that would take the run past this amount and keeps every row already charged.

`list_icp_templates`

No inputs. Returns the six prebuilt template names score_icp_fit accepts, with the actor's note on how they differ. It answers locally: no Apify run, no token, and no charge.

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.

Example output

{
  "company_domain": "ramp.com",
  "icp_score": 87,
  "icp_tier": "A",
  "lead_tag": "priority",
  "score_hiring": 25,
  "score_tech_stack": 22,
  "score_headcount": 20,
  "score_funding": 20,
  "score_industry": 0,
  "run_date": "2026-05-28"
}

Features

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

Pricing

You pay per event on Apify, billed to your own Apify account. Prices from the live pricing record, read 2026-10-16:

Event	Price per event (USD)	Fires when
`apify-default-dataset-item`	$0.05 on the Free plan, down to $0.0425 on higher Apify plans	Single result in the default dataset.
`apify-actor-start`	$0.00005	Charged when the Actor starts running. Number of events charged depends on Actor memory (one event per GB, minimum one event).

The actor's Apify page carries the current prices. Running this server consumes Apify credits.

How each call runs

Each call starts the actor run, polls it until it finishes, then reads the dataset. The run is allowed 1,800 seconds. If the run is still going when this call stops waiting, the call returns the run id and a console link instead of a timeout, so the result is never lost.

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-account-lead-scoring-fit-scorer-0-100-for-clay

Mamba Labs GTM Suite

This server is one of 103 Mamba Labs MCP servers, each backed by a dedicated Apify actor and published under @mambalabsdev on npm. The ones closest to this server:

Actor	Immutable Actor ID
GTM Hiring Signal Scraper	`D7O1SA2EqwHGsGr1P`
Tech Stack Signal Detector	`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 and Press Signal Scanner	`FS13X6dhQVgX3XOM6`

To get twenty one of them in one install, use @mambalabsdev/mcp-gtm-suite.

Built by Mamba Labs | npm | Apify Store

License

MIT

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

Available Tools

2 tools

list_icp_templatesList ICP TemplatesA

Read-onlyIdempotent

List the prebuilt ICP scoring templates score_icp_fit accepts in its template input, with the actor's own note on how they differ. Answers locally from the server: no Apify run, no token needed, and no charge. Use it before score_icp_fit when you have no scoring_config or icp_description of your own.

Inputs: no named parameters.

score_icp_fitScore ICP FitA

Read-onlyIdempotent

Score a company against your ideal customer profile (ICP) using weighted signals. Returns a 0 to 100 icp_score, an A to D icp_tier, and a per-signal breakdown as a flat, Clay-ready JSON row. Define your ICP with a prebuilt template, a JSON scoring_config, or a plain-English icp_description (which requires llm_api_key). Read-only; requires an APIFY_TOKEN and consumes Apify credits per call.

Inputs: company_domain (required), industry, template, headcount, +39 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored 2026-10-16 10:10 across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: list_icp_templates is a local, free discovery helper while score_icp_fit performs the actual scoring. There is no overlap in function or confusion about when to use each.

Naming Consistency5/5

Both names follow a consistent verb_noun snake_case pattern (list_icp_templates, score_icp_fit). The convention is predictable and readable throughout.

Tool Count3/5

With only two tools, the surface is thin: one is essentially a metadata helper for the other, leaving a single real operation. It is well-scoped for a narrow purpose but feels minimal rather than complete.

Completeness3/5

The core scoring workflow is covered, including three ways to define an ICP (template, JSON config, or plain-English description). However, there is no batch scoring, no custom template creation/management, and no way to save or retrieve past scores, which are notable gaps for a scoring service.

Maintenance

ActivityMaintained

ResponsivenessNo recent community issues

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