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alexey-pelykh/lhremote

by Various

CLI and MCP server for LinkedHelper automation — let AI assistants control LinkedIn outreach

A

MCP

alexey-pelykh/lhremote

Added 1 June 2026

#ai-automation #claude #cli #linkedhelper #linkedin-automation #mcp #mcp-server #model-context-protocol

Overview

lhremote provides a command-line interface and Model Context Protocol (MCP) server for controlling LinkedHelper, a LinkedIn automation tool. It enables AI assistants to programmatically manage LinkedIn outreach tasks such as sending connection requests and messages. The tool is built in TypeScript and is open source.

Best for

Best for
Developers building AI agents that need to automate LinkedIn outreach

Use cases

  • Automate LinkedIn outreach sequences via AI assistants
  • Programmatically send connection requests and follow-up messages
  • Integrate LinkedIn automation into MCP-compatible tools

How to use

Install

npm install -g lhremote

Tested with

Claude Desktop, Cursor, Continue

Example client config

{\n    "mcpServers": {\n        "lhremote": {\n            "command": "npx",\n            "args": ["lhremote", "mcp"]\n        }\n    }\n}

Notes

lhremote provides a command-line interface and Model Context Protocol (MCP) server for controlling LinkedHelper, a LinkedIn automation tool. It enables AI assistants to programmatically manage LinkedIn outreach tasks such as sending connection requests and messages. The tool is built in TypeScript and is open source.

7 stars on GitHub. Last updated 2026-05-29. Licensed AGPL-3.0.

Use cases

  • Automate LinkedIn outreach sequences via AI assistants
  • Programmatically send connection requests and follow-up messages
  • Integrate LinkedIn automation into MCP-compatible tools

Pros

  • Enables AI-driven control of LinkedIn automation
  • Open source with minimal dependencies
  • Uses standard MCP protocol for interoperability

Cons

  • Very low community adoption (7 GitHub stars)
  • Requires LinkedHelper to function
  • Limited documentation and support

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Enables AI-driven control of LinkedIn automation
  • Open source with minimal dependencies
  • Uses standard MCP protocol for interoperability

Cons

  • Very low community adoption (7 GitHub stars)
  • Requires LinkedHelper to function
  • Limited documentation and support
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