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outx-mcp-server

v1.1.0

Published

MCP server for OutX — LinkedIn social listening & data API

Readme

OutX MCP Server

npm version License: MIT

MCP server for the OutX LinkedIn social listening and data API. Connect AI agents like Claude, Cursor, and Claude Code to LinkedIn — create watchlists, search posts, fetch profiles, and engage, all through natural language.

What You Can Do

  • Monitor LinkedIn — Track posts by keywords, people, or companies with watchlists
  • Search & filter posts — 15+ filters: keyword, date, seniority, trending, language
  • Fetch profiles & companies — Get full LinkedIn profiles, company pages, and connections
  • Search LinkedIn — Find people by title, company, location, industry, and more
  • Message connections — Send direct messages to 1st-degree connections
  • Engage — Like and comment on posts through your LinkedIn account
  • All via natural language — Just tell your AI agent what you want

Quick Start

1. Get an API key at mentions.outx.ai/api-doc

2. Add to your AI tool (pick one):

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "outx": {
      "command": "npx",
      "args": ["-y", "outx-mcp-server"],
      "env": {
        "OUTX_API_KEY": "your-api-key"
      }
    }
  }
}

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "outx": {
      "command": "npx",
      "args": ["-y", "outx-mcp-server"],
      "env": {
        "OUTX_API_KEY": "your-api-key"
      }
    }
  }
}

Add to .mcp.json in your project:

{
  "mcpServers": {
    "outx": {
      "command": "npx",
      "args": ["-y", "outx-mcp-server"],
      "env": {
        "OUTX_API_KEY": "your-api-key"
      }
    }
  }
}

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "outx": {
      "command": "npx",
      "args": ["-y", "outx-mcp-server"],
      "env": {
        "OUTX_API_KEY": "your-api-key"
      }
    }
  }
}

3. Start using it:

"Create a watchlist to monitor LinkedIn posts about AI startups raising Series A"

Available Tools (28)

Watchlist Management

| Tool | Description | |------|-------------| | create_keyword_watchlist | Monitor LinkedIn posts matching keywords with optional required/excluded terms | | create_keyword_watchlist_by_prompt | Create a keyword watchlist from a natural-language prompt (AI generates keywords and labels) | | list_keyword_watchlists | List all keyword watchlists | | update_keyword_watchlist | Update name, scan frequency, or pause/resume | | update_keyword_watchlist_prompt | Update the prompt on an existing watchlist (regenerates all keywords and labels) | | delete_keyword_watchlist | Delete a keyword watchlist and all tracked data | | create_people_watchlist | Track posts from specific LinkedIn profiles | | list_people_watchlists | List all people watchlists | | update_people_watchlist | Update name, scan frequency, or pause/resume | | delete_people_watchlist | Delete a people watchlist | | create_company_watchlist | Monitor posts from LinkedIn company pages | | list_company_watchlists | List all company watchlists | | update_company_watchlist | Update name, scan frequency, or pause/resume | | delete_company_watchlist | Delete a company watchlist |

Posts & Engagement

| Tool | Description | |------|-------------| | get_posts | Search and filter posts from watchlists (keyword, date, seniority, trending, language, etc.) | | get_interactions | Retrieve likes and comments for posts in a watchlist with filtering, pagination, and daily graph data | | like_post | Like a post from your watchlist results | | comment_on_post | Comment on a post from your watchlist results |

LinkedIn Data API

These tools use the async LinkedIn Data API. The MCP server handles polling automatically — you get the result directly.

| Tool | Description | |------|-------------| | fetch_linkedin_profile | Fetch full LinkedIn profile by slug (name, headline, experience, education, skills) | | fetch_linkedin_posts | Fetch recent posts from profiles by URN | | fetch_linkedin_company | Fetch company page data by slug (industry, employee count, description, headquarters) | | fetch_linkedin_company_posts | Fetch recent posts from a company page with engagement data | | linkedin_send_message | Send a direct message to a 1st-degree connection | | linkedin_search_profiles | Search LinkedIn profiles by title, company, location, industry, and more | | linkedin_fetch_connections | Fetch your 1st-degree connections with keyword search and pagination | | linkedin_like_post | Like a post by activity URN | | linkedin_comment_on_post | Comment on a post by activity URN | | get_task_status | Check status of an async task manually |

Note: LinkedIn Data tools require the OutX Chrome extension to be active within the last 48 hours.

Example Prompts

Once connected, try these with your AI agent:

Social listening:

  • "Create a watchlist to monitor LinkedIn posts about AI startups raising Series A"
  • "Show me trending posts from my watchlists this week"
  • "What are VPs and Directors posting about machine learning?"
  • "Find posts mentioning our competitor from the last 7 days"

Profile & company research:

  • "Fetch the LinkedIn profile for williamhgates"
  • "Get recent posts from this prospect's profile"
  • "Get company info and recent posts for OpenAI"
  • "Search for VPs of Engineering at Google in the US"
  • "Show me my most recently added connections"

Engagement & messaging:

  • "Like the top 3 most engaging posts about product management"
  • "Comment on this post with a thoughtful response"
  • "Send a message to this connection thanking them for connecting"

Workflows:

  • "Set up a watchlist for 'looking for a CRM' and check it every 6 hours"
  • "List all my watchlists and show me posts from the sales signals one"

Prerequisites

  • Node.js 18+ — Required for the MCP server runtime
  • OutX accountSign up free and get your API key
  • OutX Chrome extension — Required for LinkedIn Data API tools (profile fetching, direct engagement). Install here

How It Works

The OutX API has two surfaces:

  1. Watchlists & Engagement API (sync) — Create watchlists to monitor LinkedIn by keywords, people, or companies. OutX scans on your schedule and stores posts. Query and engage via API.

  2. LinkedIn Data API (async) — Direct LinkedIn proxy. Fetch profiles, get posts, like, comment. All endpoints return a task ID; the MCP server polls automatically until the result is ready.

The MCP server wraps both APIs into 28 tools that any MCP-compatible AI agent can call.

Development

git clone https://github.com/outxai/outx-mcp-server.git
cd outx-mcp-server
npm install
npm run build
OUTX_API_KEY=your-key npm start

For development with auto-reload:

OUTX_API_KEY=your-key npm run dev

Documentation

Integrations

Guides & Tutorials

Links

Partnerships

Interested in a collaboration or affiliate partnership? Drop us a message at [email protected].

License

MIT