Apex by LeadShark — discovery
RemoteAbout Apex by LeadShark — discovery
Apex by LeadShark’s discovery endpoint is a no-auth MCP server that introduces the full LinkedIn operator loadout to AI agents. This minimal server provides setup guidance and starter prompts, but has no LinkedIn actions of its own.
Key features
- 01No-auth MCP discovery endpoint
- 02Apex overview and links
- 03Five-step setup guidance
- 04Copyable starter prompts
Use cases
- 01Learn what the Apex loadout provides
- 02Follow the steps to connect an account
- 03Start with prompts for discovery and action
MCP support
Exposes three no-auth informational tools—about_apex, get_setup_steps, and first_plays—over Streamable HTTP. It acts as a discovery handshake; LinkedIn operations belong to the separate authenticated full server.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://www.apex.new/mcpclaude mcp add --transport http rzere-linkedin https://www.apex.new/mcp{"mcpServers":{"rzere-linkedin":{"type":"http","url":"https://www.apex.new/mcp"}}}Open in Cursor{"servers":{"rzere-linkedin":{"type":"http","url":"https://www.apex.new/mcp"}}}Open in VS Code{"mcpServers":{"rzere-linkedin":{"type":"http","url":"https://www.apex.new/mcp"}}}{"mcpServers":{"rzere-linkedin":{"serverUrl":"https://www.apex.new/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
3This tool takes no parameters.
Details
From the project READMElinkedin-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
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:
| Tool | What it returns |
|---|---|
about_apex | What Apex is, tier pricing, trial paths, key links |
get_setup_steps | The 5-step connect flow (account → LinkedIn → 24h unlock → mount MCP → first play) |
first_plays | Copy-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
- Create a LeadShark account — free 7-day trial, no card.
- Connect the LinkedIn account the agent will operate.
- Unlock the one-time 24-hour Apex operator window (Settings → Apex Settings).
- Add
https://apex.leadshark.io/mcpto your AI app and authorize with LeadShark. - 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.
- Website: apex.new · Pricing: apex.new/pricing
- MCP setup guide: apex.leadshark.io/docs/mcp
- Agent operating guide: apex.new/agents.md
- Machine-readable index: apex.new/llms.txt
License
MIT
Comments
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.