Linkedin Prospection MCP Server

MCP server for LinkedIn prospection automation — find leads, score, qualify, personalize outreach messages, and manage your sales pipeline from any

Local serverstdio

What is the Linkedin Prospection MCP MCP server?

Linkedin Prospection MCP MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. MCP server for LinkedIn prospection automation — find leads, score, qualify, personalize outreach messages, and manage your sales pipeline from any AI agent.

What the assistant can call

Once Linkedin Prospection MCP is connected, these are the calls the assistant has available:

  • find_leads — Search LinkedIn for leads matching burnout/stress signals
  • score_lead — Score a single lead (fit 0-30 + intent 0-40 + urgency 0-30 = /100)
  • qualify_leads — Batch qualify leads with P1-P4 priority classification
  • personalize_message — Generate personalized invitation notes and DM sequences
  • run_pipeline — Run the full daily prospection pipeline
  • get_pipeline_status — Get current pipeline status and daily log
  • manage_lead — Update lead status in the pipeline

Configuration and credentials

You will need one environment variable: PROSPECTION_DIR. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

Setting it up

The server ships on npm as linkedin-prospection-mcp, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.

Choosing this one

Plenty of developer tooling servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Linkedin Prospection MCP's toolset — find_leads, score_lead, qualify_leads and 4 more — is a fair guide to whether it matches your workflow. It is maintained by gomessoaresemmanuel-cpu; worth a glance at recent repository activity before you build anything load-bearing on it.

We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the linkedin prospection mcp mcp server does with a few real requests.

Available tools

ToolWhat it does
find_leadsSearch LinkedIn for leads matching burnout/stress signals
score_leadScore a single lead (fit 0-30 + intent 0-40 + urgency 0-30 = /100)
qualify_leadsBatch qualify leads with P1-P4 priority classification
personalize_messageGenerate personalized invitation notes and DM sequences
run_pipelineRun the full daily prospection pipeline
get_pipeline_statusGet current pipeline status and daily log
manage_leadUpdate lead status in the pipeline

How to install the Linkedin Prospection MCP MCP server

{
  "mcpServers": {
    "linkedin-prospection": {
      "command": "npx",
      "args": ["-y", "linkedin-prospection-mcp"],
      "env": {
        "PROSPECTION_DIR": "/path/to/your/prospection/scripts"
      }
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

VariableDescriptionRequired
PROSPECTION_DIRFilesystem location the server is allowed to use.Optional

Example prompts to try

  • Use Linkedin Prospection MCP to find leads.
  • Use Linkedin Prospection MCP to score lead.
  • Use Linkedin Prospection MCP to qualify leads.

Frequently asked questions

It connects Linkedin Prospection MCP to MCP-compatible AI assistants such as Claude and Cursor, exposing 7 tools (find_leads, score_lead, qualify_leads, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Linkedin Prospection MCP directly.