原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Apex by LeadShark — discovery

作者:rzere版本 1.0.0i★ –i在云端运行
注册名称io.github.rzere/linkedin-mcp

安装

概览

作者提供的说明(英文原文)

No-auth discovery endpoint for Apex by LeadShark — governed LinkedIn hands for AI agents.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在云端运行
  • 传输方式: Streamable HTTP
  • 分类: 营销与社交媒体

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://www.apex.new/mcp

在终端中运行这条命令

claude mcp add --transport http linkedin https://www.apex.new/mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "linkedin": {
      "url": "https://www.apex.new/mcp"
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "linkedin": {
      "type": "http",
      "url": "https://www.apex.new/mcp"
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://www.apex.new/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月9日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 rzere 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

与“营销与社交媒体”中的其他服务器比较i

  • 星标数多于此分类中其他 3623 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 3623 个服务器的 15% 更新
  • 基础检查结果等于或优于此分类中其他 3623 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Apex by LeadShark — discovery 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.0.0)于4个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

有什么可以替代它?

同一分类中有:MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

MCP YouTube Transcript

An MCP server retrieving transcripts of YouTube videos

作者:jkawamoto正在增长★ 49512天前更新

在你的电脑上运行

Google Analytics MCP

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

作者:surendranb正在增长↓ 1088/周★ 24411天前更新

在你的电脑上运行

BibiGPT YouTube Video Summarizer

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

作者:JimmyLv正在增长★ 13712天前更新

在云端运行✓ bibigpt.co

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

linkedin-mcp

Governed LinkedIn hands for AI agents. This is the public face of Apex by LeadShark — an MCP loadout that lets Claude, ChatGPT, or Cursor operate a real LinkedIn account in plain English: find buyers, rank intent, comment, connect, and message. Every action is paced, capped, approval-queued where needed, and fully logged.

This repo contains the discovery endpoint — a minimal, dependency-free MCP server, served live at:

  • `https://www.apex.new/mcp` (alias: https://www.apex.new/linkedin-mcp)

Mount it in any MCP host and it completes the handshake instantly — no account, no auth — then briefs your agent on what the full loadout is and how to get it.

The mission

Most LinkedIn tooling automates what you already decided: schedule this post, DM whoever comments. Apex is the layer above that — the intelligence that decides what to automate and where to show up. The activation path is intelligence-first, not automation-first. In five words:

Discover demand. Engage with context.

An agent running Apex works a loop: See → Decide → Act. Find the posts and people where attention already is, figure out who's worth engaging and with what angle, then engage — inside the account's safety budget.

The loadout — 40 tools, See → Decide → Act

The full authenticated server at https://apex.leadshark.io/mcp equips your agent with:

See / discover — where is the demand? (Apex, except discover_lead_magnets)

search · discover_lead_magnets · list_signals · feed · list_recent_posts · list_person_posts · list_post_engagers · get_person_activity

Find people and companies, pull a continuously refreshed radar of prospect-rich lead-magnet posts, list your heat-scored inbound signals, turn one viral post into a warm lead list, and see the rooms a prospect is already in (get_person_activity — who they comment on, what they react to). discover_lead_magnets is available on the Pro+ MCP floor (it doubles as content market-signal); the rest of this group is Apex.

Decide / context — who is worth your time?

enrich · enrich_company · get_lead_activity

Structured profiles for a person or account: role, company, activity, connections. The agent ranks ICP fit and intent and picks the angle — comment, connect, or ignore. Built on enrich, the most-used signal in the loadout.

Act — engagement

comment_on_post · react_to_post · send_connection_request · engage_with_comment · manage_invitations

Show up where the prospect's attention already is — warm them up in public before anything lands in their inbox. Triage inbound connection requests too.

Act — messaging

list_recent_messages · get_messages_with_person · send_message · send_email

Read the inbox, pull a full thread with one person, send the DM — deduped, paced, and logged. send_email sends through your own connected Resend account (BYO key).

Company Pages

list_companies (Pro+) · comment_as_company · react_as_company · manage_company_reply_automations

List and schedule to pages you administer on Pro+; acting in the page's *voice* — commenting, reacting, and running reply-only comment automations as the page — is Apex.

Pages & captured leads (Apex)

list_lead_pages · get_page_leads · list_lead_magnet_links

Read the leads your lead magnets captured — pages with capture stats, the deduped enriched email leads for a page, and your standalone leads.sh capture links — to feed the enrich → act loop.

Automations & scheduled posts (Pro+ baseline)

create_automation · list_automations · get_automation · edit_automation · suggest_automation_settings · schedule_post_with_automation · list_scheduled_posts · get_scheduled_post · edit_scheduled_post · cancel_scheduled_post

The execution layer: comment→DM lead-magnet automations and pre-automated post scheduling. Apex decides *what* to run; these run it.

Safety, limits & history

manage_activity_limits · set_daily_dm_limit · list_actions

Check budgets before acting, adjust caps, and read the audit trail — what the agent already did, what's staged for approval, why something was refused, and the current safety mode.

Full per-tool reference (parameters, access, tiers): [apex.new/tools.md](https://www.apex.new/tools.md)

The safety model (this is the point)

Every write the agent makes shares the same daily/weekly budgets as the account's automations (DMs, replies, connections), honors the do-not-engage list, and is paced and rate-limit-aware. Actions can be refused or queued for the user's approval — and the agent is told why. Limits are calibrated from LeadShark's production LinkedIn volume, not guesswork. Agents are expected to check list_actions before acting and to work within limits rather than around them.

What this repo's server does

This discovery stub speaks MCP over Streamable HTTP (JSON-RPC 2.0 over POST, JSON responses, stateless, no SSE) and exposes three no-auth informational tools:

ToolWhat it returns
about_apexWhat Apex is, tier pricing, trial paths, key links
get_setup_stepsThe 5-step connect flow (account → LinkedIn → 24h unlock → mount MCP → first play)
first_playsCopy-paste starter prompts: verify, discover, enrich, act

It has no LinkedIn powers of its own — it's the handshake and the briefing, not the hands.

Try it

Add https://www.apex.new/mcp as a custom connector / MCP server in your AI app, or run this repo locally:

node server.mjs          # Node 18+, zero dependencies, listens on PORT (default 3000)

Handshake by hand:

curl -s -X POST http://localhost:3000/mcp \

-H 'Content-Type: application/json' \ -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-06-18","capabilities":{},"clientInfo":{"name":"curl","version":"0"}}}'

Get the full loadout

  1. Create a LeadShark account — free 7-day trial, no card.
  2. Connect the LinkedIn account the agent will operate.
  3. Unlock the one-time 24-hour Apex operator window (Settings → Apex Settings).
  4. Add https://apex.leadshark.io/mcp to your AI app and authorize with LeadShark.
  5. Ask: *"Check if you can see LeadShark Apex and list the tools available."*

Apex is $119/mo after the trial. LeadShark Pro ($39/mo) automates your lead magnet; Pro+ ($59/mo) scales automations and gated funnels; Apex is the operator loadout on top.

License

MIT

问 PopNx