Apex by LeadShark — discovery

io.github.rzere由 GitHub 账号 rzere 发布v1.0.0更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行沟通与协作商业与电商

概览

AI 生成的概览

LeadShark 旗下 Apex 的免认证发现端点,向助手介绍这套付费 LinkedIn 自动化工具集及接入方式。

可以做什么
  • 了解 Apex by LeadShark 是什么、各档位价格以及真正的认证服务器地址
  • 获取把 AI 智能体接入完整 Apex 服务器的五步流程
  • 取得首次会话可直接复制使用的起步提示词:验证、发现、丰富、行动
适用场景
适合想让助手说明 Apex 这套 LinkedIn 工具集包含什么,并引导你注册、挂载真正服务器的场景。它本身不具备任何 LinkedIn 能力,只是付费产品之前的介绍环节。
运行要求
远程 Streamable HTTP 端点,无需账号、API 密钥或请求头。README 也说明可用 Node 18+ 在本地零依赖运行。接入完整 Apex 服务器则需要 LeadShark 账号、已连接的 LinkedIn 账号并完成授权。
安装前请注意
该端点只返回信息,真正的 LinkedIn 操作在另一个需认证的服务器上。完整产品在试用期后为付费订阅,且会操作真实的 LinkedIn 账号,评论、好友邀请、私信等写入操作受额度限制、限速,有时需排队等待批准。README 提到可通过你自己的 Resend 账号和密钥发送邮件。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Apex by LeadShark — discovery,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.rzere%2Flinkedin-mcp/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "apex-by-leadshark-discovery": {
      "type": "http",
      "url": "https://www.apex.new/mcp"
    }
  }
}

README

linkedin-mcp

[Apex MCP — featured on mcpexplorer.com]

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

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:

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

Handshake by hand:

bash
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

来源:README.md,提交 3cff493

工具

3

about_apex

About Apex

Read-only: returns what Apex by LeadShark is, tier pricing, and the URL of the real authenticated MCP server. Call this first — this endpoint is a discovery stub with no LinkedIn powers.

无需输入参数。

get_setup_steps

Get setup steps

The 5-step flow to connect an AI agent to the real Apex MCP server: LeadShark account → LinkedIn → 72h Apex unlock → mount MCP → first Loadout.

无需输入参数。

first_plays

First Loadouts

Read-only: returns copy-paste starter prompts for the first session after connecting the real Apex server — verify, discover, enrich, act.

无需输入参数。

版本历史

1
  1. v1.0.0最新Sep 16, 2026

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