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LinkedIn Company Page Mapper MCP Server

LinkedIn Company Page Mapper MCP Server

Smithery Glama score npm version npm downloads license

用于 Apify 上 Mamba Labs LinkedIn Company Page Mapper actor 的 MCP 服务器。

将公司域名解析到其 LinkedIn 页面,并获取精确的关注者数量和公开的企业画像信息。

功能

将公司域名解析到其 LinkedIn 公司页面,并返回精确的关注者数量,以及 LinkedIn 在公开页面上发布的行业、声明的公司规模区间、总部、成立年份和专业领域。LinkedIn 渲染每一个数字,因此与大多数社交平台不同,这些计数可以跨列表求和。所有内容都来自未登录的页面:无需登录、无需会话 cookie、无需供应商。员工列表、员工增长和帖子互动在未登录状态下无法访问,因此不会返回。猜测的 slug 如果解析到不同的公司,将报告为 identity_mismatch。只读;需要 APIFY_TOKEN,每次调用消耗 Apify 积分。

Related MCP server: Company Firmographic Enricher MCP Server

快速开始

将此添加到您的 MCP 客户端配置中:

{
  "mcpServers": {
    "mamba-linkedin-company-presence-mapper": {
      "command": "npx",
      "args": ["-y", "@mambalabsdev/mcp-linkedin-company-presence-mapper"],
      "env": { "APIFY_TOKEN": "your-apify-token" }
    }
  }
}

前提条件

该 actor 按事件付费,每次调用消耗 Apify 积分。定价请参见 actor 页面。

示例提示

  • "gitlab.com 有多少 LinkedIn 关注者?"

  • "获取 stripe.com 的 LinkedIn 行业、规模区间和总部信息。"

  • "按 LinkedIn 关注者数量对这些域名进行排名:notion.com、figma.com、gitlab.com。"

工具和输入

工具:map_linkedin_company_presence

Input

Type

Meaning

company_domain

string

裸公司域名,例如 shopify.com。提供此域名或 handle。使用域名时,actor 会运行完整发现;使用 handle 时,它会直接跳到

company_name

string

可选。提高搜索准确性,并且是身份门检查已发现配置文件的依据,因此提供它可以减少错误匹配。

handle

string

可选。来自 linkedin.com/company/ 的公司 slug,例如 shopify。提供它可跳过发现并直接进行获取。

includeFollowerCounts

boolean

当为 "true"(默认)时,会获取配置文件页面并提取计数。设置为 "false" 仅解析配置文件 URL,这更便宜且需要

skipCache

boolean

当为 "false"(默认)时,成功的查找会缓存七天并重复使用。设置为 "true" 强制重新获取。以字符串形式发送以兼容 Clay

includeFirmographics

boolean

当为 "true"(默认)时,行业、公司规模区间、总部、成立年份和网站会与关注者数量一起从页面解析。设置为 "f

读取输出

每一行都带有每个平台的 _status 字段,这是首先要读取的字段。整个 Mamba Labs 社交产品系列的词汇表是相同的:

Status

Meaning

ok

已获取并解析,值存在

not_found

我们查找过,但没有这样的配置文件

not_extractable

配置文件存在,但值不在我们可获取的范围内

blocked

平台拒绝了我们,值得稍后重试

identity_mismatch

我们找到了一个真实的配置文件,但它属于其他人

skipped

您没有请求此平台

false 和 null 永远不可互换。 false 表示我们查找过,答案是否定的。null 表示我们无法查找。如果您要筛选没有存在的公司,请筛选 false,因为 null 行是未知的,而不是不存在的。

完整的 actor 文档

apify.com/mambalabs/linkedin-company-presence-mapper

Mamba Labs GTM 套件

Mamba Labs 构建了一系列 GTM 丰富化 actor,它们共享一个扁平的、Clay 就绪的输出约定,因此它们的行可以按 company_domain 连接,无需清理步骤。完整系列:apify.com/mambalabs

许可证

MIT

Available Tools

1 tool
map_linkedin_company_presenceMap LinkedIn Company Page PresenceA
Read-onlyIdempotent

Resolve a company domain to its LinkedIn company page and return the EXACT follower count, plus the industry, declared company size band, headquarters, founded year and specialties that LinkedIn publishes on the public page. LinkedIn renders every digit, so unlike most social platforms these counts can be summed across a list. Everything comes from the logged out page: no login, no session cookie, no vendor. Employee lists, employee growth and post engagement are NOT reachable logged out and are not returned. A guessed slug that resolves to a different company is reported as identity_mismatch. Read only; requires an APIFY_TOKEN and consumes Apify credits per call.

ParametersJSON Schema
NameRequiredDescriptionDefault
handleNoOptional. The company slug from linkedin.com/company/<slug>, for example shopify. Supplying it skips discovery and goes straight to the fetch.
skipCacheNoWhen "false" (default) a successful lookup is cached for seven days and reused. Set "true" to force a fresh fetch. Sent as a string for Clay compatibility.
company_nameNoOptional. Improves search accuracy and is what the identity gate checks a discovered profile against, so supplying it reduces wrong matches.
company_domainNoBare company domain, for example shopify.com. Supply this or a handle. With a domain the actor runs full discovery; with a handle it skips straight to the fetch.
includeFirmographicsNoWhen "true" (default) industry, company size band, headquarters, founded year and website are parsed off the page alongside the follower count. Set "false" for the URL and follower count only. Sent as a string for Clay compatibility.
includeFollowerCountsNoWhen "true" (default) the profile page is fetched and the counts are extracted. Set "false" to resolve the profile URL only, which is cheaper and needs no proxy. Sent as a string for Clay compatibility.

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark readOnly, openWorld, idempotent, non-destructive. The description goes well beyond by disclosing logged-out access, exact digit rendering, non-reachability of certain data, identity_mismatch handling for guessed slugs, and the cost/credit implications. None of this contradicts the annotations; it enriches them.

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?

Six sentences, all substantive: purpose, output list, a distinguishing fact (summable counts), access mode, exclusions, and an identity edge case. Every sentence carries information an agent needs; there is no filler or redundant restating of annotations.

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?

With no output schema and zero required parameters, the description carries full responsibility for usability. It covers what is returned, what is not, how mismatches are reported, auth requirements, and cost implications. An agent has enough to decide and invoke correctly without guessing.

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% and each parameter already has detailed descriptions, so the baseline is 3. The tool description adds some context around discovery vs. direct fetch and the Clay string conversion, but these are largely echoed in the schema. It does not introduce new parameter-level semantics beyond what the schema already conveys.

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 opens with a precise verb-resource pair ('Resolve a company domain to its LinkedIn company page') and enumerates the exact outputs: follower count, industry, size band, HQ, founded year, specialties. It clearly differentiates from typical social-platform tools by noting counts are exact and summable, leaving no ambiguity about the function.

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 clearly states what the tool returns and, importantly, what it does NOT return (employee lists, growth, engagement) and that no login or session is needed. It also mentions the APIFY_TOKEN requirement and credit consumption. While it doesn't name a specific alternative tool, there are no siblings, and the conditions for choosing this approach (public logged-out data) are explicit enough.

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. 1 tool updatev1.0.0
    • First observedmap_linkedin_company_presence

TDQS

A4.5/5.0

Scored across 1 tool

Disambiguation5/5

With exactly one tool, no selection ambiguity exists. The tool's name and description clearly define it as a single-purpose LinkedIn company page lookup.

Naming Consistency5/5

The single tool uses descriptive snake_case with a clear verb-object pattern that matches the server's stated purpose, so the naming is coherent and unsurprising.

Tool Count4/5

One tool is slightly narrower than a typical MCP server, but it is substantive and fully aligned with the server's declared purpose. The count feels minimal rather than bloated or trivial.

Completeness4/5

The tool covers the logged-out LinkedIn page mapping surface well, returning the key company fields and explicitly documenting unavailable data types. It is not fully complete because there is no batch or multi-domain mapping capability.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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