Controls LinkedHelper through MCP and CLI for LinkedIn accounts, campaigns, messaging, profiles, and engagement workflows.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
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๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Lhremote.
find-appDetect running LinkedHelper application instances and their CDP connection details.
launch-appLaunch the LinkedHelper application with remote debugging enabled.
quit-appQuit the LinkedHelper application.
list-accountsList available LinkedHelper accounts. Returns account ID, LinkedIn ID, name, and email for each account.
start-instanceStart a LinkedHelper instance for a LinkedIn account.
stop-instanceStop a running LinkedHelper instance.
alexey-pelykh/lhremote MCP server exposes LinkedHelper automation through both MCP tools and a command-line interface. It can find a running LinkedHelper application, launch or quit it, list available LinkedIn accounts, start or stop account instances, and report connection or database status.
Campaign workflows include creating campaigns from YAML or JSON, reading and exporting configurations, changing metadata, archiving or permanently erasing campaigns, and starting or stopping execution. Agents can inspect campaign status and statistics, retry selected people, manage action chains, move people between actions, and maintain campaign or action exclusion lists. LinkedIn profile URLs can be imported into campaign target lists, and assigned people can be listed or removed.
The README also documents capabilities beyond the supplied campaign tool list, including cached profile queries, messaging history and reply checks, LinkedIn actions such as profile visits and engagement, feed and post queries, profile enrichment, search-related helpers, action discovery, and throttle or budget monitoring.
alexey-pelykh/lhremote MCP server communicates with the local LinkedHelper desktop application using Chrome DevTools Protocol connection details. The workflow starts by finding an existing application or launching one with remote debugging enabled. After an account is selected, an instance can be started before campaign or LinkedIn actions are used.
The MCP entry point runs as the mcp subcommand. The CLI exposes corresponding commands for the documented MCP operations, with JSON output options on many commands. Campaign creation accepts a file or inline YAML/JSON configuration. Starting a campaign is asynchronous, so status and statistics commands are used to monitor execution.
The project requires Node.js 24 or newer and the LinkedHelper desktop application. LinkedHelper requires a paid subscription. Install the npm package globally or run it through npx; for Claude Desktop, configure a local command using npx, the lhremote package, and the mcp subcommand.
A typical operating sequence is to detect or launch LinkedHelper, list accounts, start an account instance, inspect available action types, create a campaign, import profile URLs, start the campaign, and monitor its status. Campaign and targeting commands accept IDs, URLs, files, or inline values depending on the operation.
alexey-pelykh/lhremote MCP server depends on a locally installed LinkedHelper application rather than operating as a standalone LinkedIn client. Its documented prerequisites include a paid LinkedHelper subscription. LinkedIn monitors automated activity, so the project points users to its rate-limiting guidance. Permanently erasing a campaign removes its related database data and cannot be undone; campaign deletion is described as an archival operation instead.
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