mcp-domain-to-linkedin-url-resolver
Resolve a company domain or name to its LinkedIn company URL and return a flat JSON row with confidence, social links, and firmographics.
Resolve a single company using
company_domain(e.g.,stripe.com) orcompany_name.Get the LinkedIn company URL, slug, resolution method, and confidence score (high/medium/low).
Receive social links (Facebook, Instagram, X, YouTube) and firmographic fields like employee count, industry, HQ, follower count, description, logo, and founded year.
Read-only and idempotent; requires an
APIFY_TOKENand consumes Apify credits per call.Per README, the underlying actor also supports batch domain lists,
batchSize,includeFirmographics, andskipCache, though the MCP schema only exposescompany_domainandcompany_name.
Domain to LinkedIn URL Resolver MCP Server
An MCP server that resolves a company domain or name to its LinkedIn company URL. It wraps the Mamba Labs Domain to LinkedIn URL Resolver 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 or a company name and it finds the matching LinkedIn company page, with a confidence of high, medium, or low so you know how much to trust it, plus the company's Facebook, Instagram, X, and YouTube links, all in one flat row. Firmographics (employee count, industry, headquarters, follower count, description) are added when you set includeFirmographics to true; they are off by default and null when off. Pass domains to resolve a list in one call ready for Clay, a CRM, or an AI agent workflow. All of the resolution 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-linkedin-resolver": {
"command": "npx",
"args": ["-y", "@mambalabsdev/mcp-domain-to-linkedin-url-resolver"],
"env": {
"APIFY_TOKEN": "your-apify-token"
}
}
}
}Get your token at https://console.apify.com/account/integrations, paste it in, and restart Claude Desktop. The resolve_linkedin_url tool will be available.
Prerequisites
Node.js 18 or newer
An Apify account with an API token
Example prompts
"Find the LinkedIn page for stripe.com."
"What is the LinkedIn company URL for openai.com? Include the confidence score."
"Resolve the company named Figma to its LinkedIn URL and firmographics."
"Get the LinkedIn URL, employee count, and industry for datadoghq.com, with firmographics on."
"Resolve the LinkedIn pages for stripe.com, notion.so, and figma.com."
Inputs
company_domain(optional): the bare company domain, nohttps://and no trailing slash. Example:stripe.comcompany_name(optional): the company name.domains(optional, array): a list of bare domains resolved in one run, one row per domain.batchSize(optional, integer): how many domains from the list are resolved at once. 1 to 10. Default 2.includeFirmographics(optional, boolean): also read the public LinkedIn company page foremployee_count_approx,industry,hq_location,follower_count, andcompany_description. Default false. Those fields are null when it is off. The string forms"true"and"false"are accepted too.skipCache(optional, boolean): ignore the 7 day cache and resolve again. Default false. The string forms are accepted too.
Provide at least one of company_domain, company_name, or domains. If a domain and a name are both given, the domain takes priority.
Output
The tool returns the actor's flat JSON row per company: company_domain, company_name, linkedin_company_url, linkedin_slug, resolution_method, confidence (high, medium, or low), facebook_url, instagram_url, twitter_url, youtube_url, the firmographic fields employee_count_approx, industry, hq_location, follower_count, company_description, logo_url, and founded_year (null unless includeFirmographics is true), slug_mismatch, run_date, degraded, and degradation_reason.
Example output
Run with includeFirmographics set to true.
{
"company_domain": "linear.app",
"company_name": "Linear",
"linkedin_company_url": "https://www.linkedin.com/company/linear-app",
"linkedin_slug": "linear-app",
"resolution_method": "google_search",
"confidence": "high",
"industry": "Software Development",
"employee_count_approx": "201",
"hq_location": "San Francisco, California, United States",
"run_date": "2026-05-28"
}Features
Google search plus URL pattern matching for high accuracy
Fixes the LinkedIn URL gaps in Clay native enrichment
Confidence scoring (high, medium, low) and resolution_method
Social links on every row; firmographics (employee count, industry, HQ) when
includeFirmographicsis trueOne domain or a list per call
Pricing
Domain to LinkedIn URL Resolver is pay per event on Apify.
Event | Price | Fires when |
| $0.00005 | Once per run, on start, one event per GB of memory (minimum one). Apify's start event. |
| $0.006 (FREE tier), down to $0.0051 on GOLD and above | Once per row written to the dataset. |
The tool starts the actor run and polls it to a finished status, so a long run is not cut off at 300 seconds. A run that does not succeed comes back as an error with its run ID and status.
Full actor documentation
This server is a thin client and holds no resolution logic. For the complete input and output reference, pricing, and run history, see the Apify Store page:
https://apify.com/mambalabs/domain-to-linkedin-url-resolver
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.
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Built by Mamba Labs | npm | Apify Store
License
MIT
Built by Mamba Labs. https://apify.com/mambalabs
Available Tools
1 toolresolve_linkedin_urlResolve LinkedIn URLARead-onlyIdempotent
Resolve a company domain or name to its LinkedIn company URL. Returns the LinkedIn URL with a confidence score, plus firmographics such as employee count, industry, and headquarters, and social links, as a flat, Clay-ready JSON row. Provide at least one of company_domain or company_name. Read-only; requires an APIFY_TOKEN and consumes Apify credits per call.
| Name | Required | Description | Default |
|---|---|---|---|
| company_domain | No | Bare company domain without https:// and without a trailing slash. Example: stripe.com. Required if company_name is not provided. | |
| company_name | No | Company name. Required if company_domain is not provided. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds context about requiring APIFY_TOKEN and consuming credits, which is valuable beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, efficiently conveying purpose, inputs, outputs, and constraints. No filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description fully specifies the return content (firmographics, confidence score, social links) and format (flat, Clay-ready JSON row). All relevant aspects are covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description further clarifies that company_domain should be 'bare' without protocol or trailing slash, providing an example. This adds meaningful detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves a company domain or name to its LinkedIn URL and lists the returned data (confidence score, firmographics, social links). It provides a specific verb ('resolve') and resource ('LinkedIn URL'), making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states the input requirement ('provide at least one of company_domain or company_name') and notes prerequisites (APIFY_TOKEN, credit consumption). While it does not mention alternatives, no siblings exist, so this is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.3- First observed
resolve_linkedin_url
TDQS
Scored across 1 tool
With only one tool, there is no risk of ambiguity between tools. The single tool has a distinct and clear purpose.
The single tool name 'resolve_linkedin_url' follows a clear verb_noun pattern, consistent with best practices.
One tool is at the lower end of the range. While it serves a specific resolver function, the surface is minimal and might feel thin for broader use cases.
For the stated purpose of resolving a domain or name to a LinkedIn URL with firmographics, the single tool fully covers the intended operation with no obvious gaps.
Maintenance
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