A
licenseNot graded
qualityD
maintenanceDomain -> company intelligence for AI agents. Look up company name, country, contacts, and social profiles from any MCP-compatible client.
6
MIT
Company Firmographic Enricher MCP Server
by mambalabsdev
This server enriches company domains into structured firmographic data using a single MCP tool, powered by Apify.
Enrich a single domain: Provide a bare domain (e.g.,
stripe.com) to retrieve employee band, industry, HQ location, founded year, revenue estimate, logo URL, and description.Batch enrichment: Supply a list of domains for concurrent bulk processing, with configurable
batchSize(default 5, max 10).Fallback company name: Optionally pass a
company_nameas a label when the company's webpage doesn't expose one.Cache control: Set
skipCacheto true to force a fresh enrichment, bypassing the 7-day result cache.Source provenance: Every result includes a
source_signalsarray (e.g.,schema.org/OrganizationJSON-LD and HTML meta tags) and adata_completenessscore.Clay-ready output: Returns flat JSON rows suitable for use in Clay or similar enrichment pipelines.
Read-only operation: The tool is idempotent and non-destructive; it requires an
APIFY_TOKENand consumes Apify credits per call.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Company Firmographic Enricher MCP ServerEnrich stripe.com: employees, industry, HQ, founded year, and revenue estimate."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Company Firmographic Enricher MCP Server
An MCP server that exposes the Mamba Labs Company Firmographic Enricher as a single tool. Install one package and give your MCP client a way to turn a company domain into structured firmographics, wrapping the Mamba Labs actor on Apify and returning Clay-ready flat JSON with source provenance.
What's Inside
Related MCP server: mcp-gtm-tech-stack-signal-scraper
What it does
This server gives an AI client one tool:
enrich_company_firmographics: enrich a company domain into employee band, industry, HQ, founded year, revenue estimate, logo, and description, parsed from the company's schema.org/Organization JSON-LD and HTML meta tags. Every record includes asource_signalsarray and adata_completenessscore.
All of the work runs on Apify. This package is a thin client that routes the tool call to 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": {
"company-firmographic-enricher": {
"command": "npx",
"args": ["-y", "@mambalabsdev/mcp-company-firmographic-enricher"],
"env": {
"APIFY_TOKEN": "your-apify-token"
}
}
}
}Get your token at https://console.apify.com/account/integrations, paste it in, and restart Claude Desktop. The tool will be available.
Prerequisites
Node.js 18 or newer
An Apify account with an API token
Example prompts
"Enrich stripe.com: employees, industry, HQ, founded year, and revenue estimate."
"What firmographics can you find for gitlab.com, and how complete is the data?"
"Pull company firmographics for these domains: stripe.com, gitlab.com, notion.so."
"Find the employee band and HQ location for acme.com."
Tool and inputs
enrich_company_firmographics:
domain(string): bare company domain to enrich, e.g. stripe.com. Provide this ordomains.company_name(string): optional company name, used as a fallback label when the page does not expose one.domains(array): list of bare domains for batch processing. Takes precedence overdomain.batchSize(number): domains enriched concurrently per wave in batch mode. Default 5, maximum 10.skipCache(boolean): force a fresh enrichment and ignore the 7 day result cache.
Full actor documentation
For the complete input and output reference, pricing, and run history, see the Company Firmographic Enricher actor on the Apify Store (canonical immutable Actor ID URL):
https://apify.com/mambalabs/YlUtLWjfPpqykmB8g
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 toolenrich_company_firmographicsEnrich Company FirmographicsARead-onlyIdempotent
Enrich a company domain into structured firmographics: employee band, industry, HQ, founded year, revenue estimate, logo, and description, with source provenance. Parsed from the company's schema.org/Organization JSON-LD and HTML meta tags and returned as a flat, Clay-ready JSON row with a source_signals array and a data_completeness score. Read-only; requires an APIFY_TOKEN and consumes Apify credits per call.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | Bare company domain to enrich, e.g. stripe.com. Provide this or domains. | |
| company_name | No | Optional company name, used as a fallback label when the page does not expose one. | |
| domains | No | List of bare domains for batch processing. Takes precedence over domain. | |
| batchSize | No | Domains enriched concurrently per wave in batch mode. Default 5, maximum 10. | |
| skipCache | No | Force a fresh enrichment and ignore the 7 day result cache. |
TDQS
A4.5/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds valuable behavioral details: the source of data (schema.org JSON-LD and HTML meta tags), the output format (flat JSON row with source_signals and data_completeness score), and the existence of a cache (skipCache parameter). 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences covering purpose, technical detail, and constraints. It is front-loaded with the key purpose and structured logically.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is complete given the context. It explains the output format despite no output schema, mentions caching behavior, and covers prerequisites. No gaps are evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (all 5 parameters have descriptions). The description adds no new parameter-level information beyond what the schema already provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool enriches a company domain into structured firmographics, listing specific output fields (employee band, industry, HQ, etc.). It uses a specific verb 'enrich' and resource 'company domain', and distinguishes itself from any potential siblings by being specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides contextual usage guidance: it is read-only, requires an APIFY_TOKEN, and consumes Apify credits. While it doesn't explicitly state when not to use it or alternatives (none provided), the constraints are clear enough for an AI agent to decide.
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. Dates show when Glama detected each change.
1 tool update
v1.0.0- First observed
enrich_company_firmographics
TDQS
A4.5/5.0
Disambiguation5/5
With only one tool, there is no ambiguity or overlap. The single tool has a clear, well-defined purpose.
Naming Consistency5/5
The single tool name 'enrich_company_firmographics' follows a clear verb_noun pattern, which is consistent within the set.
Tool Count4/5
One tool is slightly thin but appropriate for a narrow-scope server focused solely on enriching firmographics from a company domain. It covers the core functionality without unnecessary bloat.
Completeness4/5
For the stated purpose of enriching firmographics from a domain, the single tool covers the primary operation. Minor gaps like batch enrichment or caching are absent but not critical for a read-only enrichment service.
Maintenance
ActivityMaintained
ResponsivenessNo issues
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Company & brand data by domain or ticker/ISIN: industry, headcount, HQ, social, colors, logos.
Domain & brand intelligence: company enrichment, tech stack detection, brand research.
TAM mapping, company discovery, contact intelligence, and technographics across 65M+ B2B domains.
B2B data enrichment for 375M+ companies: legal entities, corporate hierarchies, and contacts.
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