Apex by LeadShark — discovery

io.github.rzere由 GitHub 帳號 rzere 發布v1.0.0更新於 Oct 24, 2026

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

已驗證Streamable HTTP可網頁執行溝通與協作商業與電商

概覽

AI 產生的概覽

LeadShark 旗下 Apex 的免驗證探索端點，向助理說明這套付費 LinkedIn 自動化工具組與接入方式。

可以做什麼
  • 了解 Apex by LeadShark 是什麼、各方案價格，以及真正需驗證的伺服器位址
  • 取得把 AI 代理接入完整 Apex 伺服器的五步流程
  • 取得第一次工作階段可直接複製使用的起始提示詞：驗證、探索、補充資料、採取行動
適用情境
適合想讓助理說明 Apex 這套 LinkedIn 工具組包含什麼，並引導你註冊、掛載真正伺服器的情境。它本身不具備任何 LinkedIn 能力，只是付費產品之前的介紹環節。
執行需求
遠端 Streamable HTTP 端點，不需帳號、API 金鑰或請求標頭。README 也說明可用 Node 18+ 在本機零相依套件執行。接入完整 Apex 伺服器則需要 LeadShark 帳號、已連結的 LinkedIn 帳號並完成授權。
安裝前請注意
此端點只回傳資訊，真正的 LinkedIn 操作在另一個需驗證的伺服器上。完整產品在試用期後為付費訂閱，且會操作真實的 LinkedIn 帳號，留言、邀請、私訊等寫入動作受額度限制、限速，有時需排隊等待核准。README 提到可透過你自己的 Resend 帳號與金鑰寄送電子郵件。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Apex by LeadShark — discovery，將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式，或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南，先向你展示發布者、端點和登入方式，經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.rzere%2Flinkedin-mcp/install.md，並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前，先告訴我它的發布者、端點和登入方式，等我確認。不要把 API 金鑰寫進命令或我會提交的檔案；問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "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

來源：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.

無需輸入參數。

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.

無需輸入參數。

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.

無需輸入參數。

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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