Which integrations are available for this server?

Enables cross-referencing [Gmail](/mcp/servers/integrations/gmail) contacts with LinkedIn profiles and finding LinkedIn profiles for email correspondents, facilitating contact research and networking based on email interactions. Allows pulling LinkedIn profiles and recent posts for upcoming meeting attendees, enabling meeting preparation and relationship intelligence for scheduled events. Supports exporting LinkedIn prospect summaries and network data to [Notion](/mcp/servers/integrations/notion) for CRM note-taking and relationship management workflows. Enables adding LinkedIn profile summaries and professional intelligence to [Obsidian](/mcp/servers/integrations/obsidian) notes for personal knowledge management and CRM purposes.

LinkedIn Intelligence MCP Server

Transform LinkedIn from a social network into your AI-powered business intelligence platform.

The LinkedIn MCP Server connects Claude Desktop directly to LinkedIn's data layer, enabling natural language conversations that extract insights, automate engagement, and supercharge your professional networking—all without leaving your AI assistant.

Why LinkedIn MCP?

Traditional LinkedIn	With LinkedIn MCP
Manually scroll through feeds	Ask Claude: "Show me posts from my network about AI this week"
Export connections to spreadsheets	Ask Claude: "Analyze my network by industry and seniority"
Guess at optimal posting times	Ask Claude: "When do my posts get the most engagement?"
Research prospects one-by-one	Ask Claude: "Get profiles for these 10 decision-makers"
Copy-paste between tools	Seamless integration with Gmail, Calendar, and other MCPs

The MCP Ecosystem Advantage

LinkedIn MCP becomes exponentially more powerful when combined with other Claude Desktop integrations:

Gmail MCP → "Find LinkedIn profiles for everyone who emailed me this week about partnerships"
Google Calendar MCP → "Who am I meeting tomorrow? Pull their LinkedIn profiles and recent posts"
Notion/Obsidian MCP → "Add this prospect's LinkedIn summary to my CRM notes"
File System MCP → "Export my network analytics to a CSV for my quarterly report"

This isn't just another LinkedIn tool—it's the bridge that connects your professional network to your entire AI-powered workflow.

Use Cases by Role

Turn LinkedIn into your AI-powered prospecting engine.

Your Daily Workflow, Supercharged

Before	After (with LinkedIn MCP)
2 hours researching prospects	"Get me profiles and recent activity for these 20 leads"
Generic outreach messages	"What topics does [prospect] post about? Draft a personalized message"
Missing engagement signals	"Alert me when target accounts post about [pain point]"

Key Tools for SDRs

🔍 Research & Intelligence ├── search_people() - Find prospects by company, title, keywords ├── get_profile() - Deep-dive into prospect backgrounds ├── get_profile_posts() - See what they care about └── batch_get_profiles() - Research entire account lists at once 📬 Outreach & Engagement ├── send_connection_request() - Personalized invites at scale ├── send_message() - Direct outreach to connections ├── like_post() / comment_on_post() - Warm up cold prospects └── react_to_post() - Show genuine engagement 📊 Pipeline Intelligence ├── get_conversations() - Track outreach threads ├── analyze_engagement() - See what messaging resonates └── get_pending_invitations() - Manage your connection pipeline

Example Prompts for SDRs

"Search for VPs of Engineering at Series B fintech companies in NYC"
"What has [prospect name] posted about in the last month? Summarize the themes"
"Send connection requests to these 10 people with a message about [topic]"
"Show me which of my connection requests from last week were accepted"
"Cross-reference my Gmail contacts with LinkedIn—who should I connect with?"

Map relationships and identify partnership opportunities at scale.

Strategic Intelligence Gathering

Challenge	LinkedIn MCP Solution
Finding decision-makers	"Who are the BD leads at [company]? Get their profiles"
Understanding company priorities	"What is [company] posting about? Any partnership announcements?"
Tracking competitor partnerships	"Show me [competitor]'s recent posts mentioning partnerships or integrations"
Warm introductions	"Which of my connections work at or are connected to [target company]?"

Key Tools for BD Professionals

🏢 Company Intelligence ├── search_companies() - Find potential partners by criteria ├── get_profile_posts() - Track company announcements └── search_people() - Identify key stakeholders 🔗 Relationship Mapping ├── get_connections() - Your network inventory ├── get_network_stats() - Network composition analysis └── get_profile_contact_info() - Direct contact details 📈 Opportunity Tracking ├── get_feed() - Monitor partnership signals ├── analyze_content_performance() - Understand what resonates └── generate_engagement_report() - Track relationship building

Example Prompts for BD

"Find AI/ML companies that have posted about seeking partnerships in the last 30 days"
"Map my path to the CEO of [target company]—who do I know there?"
"What integrations or partnerships has [company] announced this quarter?"
"Get me the profiles of everyone with 'Partnerships' in their title at these 5 companies"
"Summarize the recent posts from decision-makers at my target accounts"

Data-driven content strategy for thought leadership.

Build Your Presence Strategically

Guesswork	Data-Driven (with LinkedIn MCP)
Post whenever, hope for engagement	"When do my posts get the most engagement? Analyze my last 50 posts"
Random hashtags	"Which hashtags drive the most reach for my content?"
Wonder what resonates	"What topics get the most comments from my audience?"
Inconsistent posting	Schedule content for optimal times automatically

Key Tools for Brand Builders

📝 Content Creation ├── create_post() - Publish directly from Claude ├── create_draft() - Save ideas for later ├── analyze_draft_content() - Get AI feedback before posting └── schedule_post() - Queue content for peak times 📊 Performance Analytics ├── analyze_optimal_posting_times() - Find your best windows ├── analyze_hashtag_performance() - Optimize discoverability ├── analyze_content_performance() - Track what works └── generate_engagement_report() - Full performance review 🎯 Audience Intelligence ├── get_post_comments() - Understand audience reactions ├── get_post_reactions() - See who engages ├── analyze_post_audience() - Demographics of engagers └── analyze_engagement() - Deep engagement metrics

Example Prompts for Brand Builders

"Analyze my last 30 posts—which topics drove the most engagement?"
"What time of day should I post to maximize reach with my audience?"
"Draft a post about [topic] optimized for engagement based on what works for me"
"Schedule this post for my optimal posting time tomorrow"
"Which of my posts this month could be repurposed into a series?"

Multi-account insights and competitor analysis for agency professionals.

Agency-Grade Intelligence

Manual Process	Automated with LinkedIn MCP
Weekly competitor audits	"Compare posting frequency and engagement across these 5 competitors"
Client reporting	"Generate an engagement report for [client profile]"
Trend spotting	"What topics are trending in [industry] this week?"
Benchmarking	"How does my client's engagement rate compare to competitors?"

Key Tools for Agencies

🔍 Competitive Analysis ├── get_profile_posts() - Track competitor content ├── analyze_content_performance() - Benchmark strategies ├── analyze_engagement() - Compare engagement metrics └── search_people() - Monitor competitor teams 📋 Client Management ├── generate_engagement_report() - Automated reporting ├── analyze_optimal_posting_times() - Client-specific insights ├── analyze_hashtag_performance() - Strategy optimization └── get_post_analytics() - Detailed post breakdowns 📈 Market Intelligence ├── get_feed() - Industry trend monitoring ├── search_companies() - Market landscape mapping └── batch_get_profiles() - Bulk research capabilities

Example Prompts for Agencies

"Compare the posting strategy of [client] vs their top 3 competitors"
"Generate a monthly engagement report for [client profile]"
"What content themes are driving the most engagement in the [industry] space?"
"Track what [competitor] has posted about our client's product category"
"Create a benchmark report: my client vs industry average engagement"

Build talent pipelines with AI-powered sourcing.

Recruiting, Reimagined

Traditional Sourcing	AI-Powered Sourcing
Boolean searches, one at a time	"Find senior engineers at FAANG who've posted about leaving big tech"
Manual candidate research	"Summarize this candidate's career trajectory and recent interests"
Cold outreach fatigue	"What does this candidate care about? Draft a personalized InMail"
Lost in spreadsheets	Integrated pipeline tracking with other MCPs

Key Tools for Recruiters

🎯 Candidate Sourcing ├── search_people() - Advanced candidate search ├── get_profile() - Comprehensive candidate profiles ├── get_profile_skills() - Skills and endorsements ├── batch_get_profiles() - Research candidate lists 💬 Candidate Engagement ├── get_profile_posts() - Understand candidate interests ├── send_connection_request() - Personalized outreach ├── send_message() - Direct candidate communication └── get_conversations() - Track outreach threads 📊 Pipeline Analytics ├── get_pending_invitations() - Monitor connection pipeline ├── get_connections() - Your talent network └── get_network_stats() - Network composition

Example Prompts for Recruiters

"Find product managers at [company] who've been in role 2+ years"
"What has this candidate posted about? What motivates them?"
"Get profiles for all engineers at [company] with ML in their title"
"Draft a personalized connection message for [candidate] based on their interests"
"Who in my network is connected to this candidate for a warm intro?"

Maximize reach and engagement with data-driven content strategies.

Content Strategy on Autopilot

Content Struggle	LinkedIn MCP Solution
What should I post about?	"What topics are getting engagement in my niche this week?"
Writer's block	"Based on my top posts, generate 5 content ideas"
Engagement drops	"Why did my engagement drop last week? Analyze the data"
Audience mystery	"Who's engaging with my content? Profile my active followers"

Key Tools for Creators

📝 Content Workflow ├── create_draft() - Save ideas and drafts ├── analyze_draft_content() - AI-powered content review ├── schedule_post() - Automated publishing └── list_scheduled_posts() - Manage content calendar 📊 Deep Analytics ├── analyze_content_performance() - Content type analysis ├── analyze_hashtag_performance() - Hashtag ROI ├── analyze_optimal_posting_times() - Peak engagement windows └── generate_engagement_report() - Comprehensive analytics 🎯 Engagement Optimization ├── get_post_comments() - Comment analysis ├── reply_to_comment() - Community management ├── analyze_post_audience() - Audience demographics └── get_post_reactions() - Reaction breakdown

Example Prompts for Creators

"Analyze my content performance over the last 90 days—what's working?"
"Which of my posts should I turn into a content series?"
"What are the top creators in [niche] posting about this month?"
"Review this draft and suggest improvements for engagement"
"Build me a content calendar for next week based on my best-performing topics"

Quick Start

Prerequisites

Python 3.11+
uv (recommended) or pip
Claude Desktop
LinkedIn account

Installation

# Clone the repository git clone https://github.com/southleft/linkedin-mcp.git cd linkedin-mcp # Set up environment uv venv && source .venv/bin/activate uv pip install -e ".[dev]" # Create data directory mkdir -p data

Authentication

Export your LinkedIn cookies from an active browser session:

Log into LinkedIn in Chrome/Firefox
Open DevTools → Application (Chrome) or Storage (Firefox)
Find Cookies → https://www.linkedin.com
Copy li_at and JSESSIONID values

Create data/session_cookies.json:

{ "li_at": "YOUR_LI_AT_COOKIE_VALUE", "JSESSIONID": "\"ajax:1234567890123456789\"" }

Note: The JSESSIONID typically includes escaped quotes. Copy exactly as shown in your browser.

Claude Desktop Configuration

Add to your Claude Desktop config file:

Platform	Config Location
macOS	`~/Library/Application Support/Claude/claude_desktop_config.json`
Windows	`%APPDATA%\Claude\claude_desktop_config.json`
Linux	`~/.config/Claude/claude_desktop_config.json`

{ "mcpServers": { "linkedin": { "command": "uv", "args": ["run", "linkedin-mcp"], "cwd": "/absolute/path/to/linkedin-mcp", "env": { "LINKEDIN_API_ENABLED": "true", "LOG_LEVEL": "INFO" } } } }

Important: The cwd must be an absolute path to the project directory.

Restart Claude Desktop and verify with: "Use debug_context to check LinkedIn MCP status"

Complete Tool Reference

Diagnostic

debug_context() - Server initialization status and configuration

Profile Tools

get_my_profile() - Your LinkedIn profile
get_profile(profile_id) - Any profile by public ID
get_profile_contact_info(profile_id) - Contact information
get_profile_skills(profile_id) - Skills and endorsements
get_profile_sections() - Editable profile sections
get_profile_completeness() - Profile completeness score
get_network_stats() - Network size and demographics
batch_get_profiles(profile_ids) - Multiple profiles efficiently

Profile Management (browser automation)

update_profile_headline(headline) - Update headline
update_profile_summary(summary) - Update about section
upload_profile_photo(photo_path) - Upload profile photo
upload_background_photo(photo_path) - Upload banner photo
add_profile_skill(skill_name) - Add a skill
check_browser_automation_status() - Browser availability

Feed & Posts

get_feed(limit) - Your feed posts
get_profile_posts(profile_id, limit) - Posts from a profile
create_post(text, visibility) - Create a new post
get_post_reactions(post_urn) - Reactions on a post
get_post_comments(post_urn) - Comments on a post

Content Creation & Scheduling

analyze_draft_content(content, industry) - Content analysis with suggestions
create_draft(content, title, tags) - Save a content draft
list_drafts(tag) - List content drafts
get_draft(draft_id) - Get a specific draft
update_draft(draft_id, content, title, tags) - Update a draft
delete_draft(draft_id) - Delete a draft
publish_draft(draft_id, visibility) - Publish a draft as a post
schedule_post(content, scheduled_time, visibility, timezone) - Schedule a post
list_scheduled_posts(status) - View scheduled posts
get_scheduled_post(job_id) - Scheduled post details
update_scheduled_post(job_id, ...) - Update scheduled post
cancel_scheduled_post(job_id) - Cancel scheduled post

Engagement

like_post(post_urn) - Like a post
react_to_post(post_urn, reaction) - React (LIKE, CELEBRATE, SUPPORT, LOVE, INSIGHTFUL, FUNNY)
unreact_to_post(post_urn) - Remove reaction
comment_on_post(post_urn, text) - Comment on a post
reply_to_comment(comment_urn, text) - Reply to a comment

Messaging

get_conversations(limit) - Messaging conversations
get_conversation(conversation_id) - Full conversation history
send_message(profile_id, text) - Send a direct message
send_bulk_messages(profile_ids, text) - Send to multiple recipients (max 25)

Connections

get_connections(limit) - Your connections
send_connection_request(profile_id, message) - Send connection invite
remove_connection(profile_id) - Remove a connection
get_pending_invitations(sent) - View pending invites
accept_invitation(invitation_id, shared_secret) - Accept connection request
reject_invitation(invitation_id, shared_secret) - Reject connection request

Search

search_people(keywords, limit, connection_of, current_company) - Search for people
search_companies(keywords, limit) - Search for companies

Analytics

get_post_analytics(post_urn) - Engagement metrics for a post
analyze_engagement(post_urn, follower_count) - Deep engagement analysis
analyze_content_performance(profile_id, post_limit) - Content type analysis
analyze_optimal_posting_times(profile_id, post_limit) - Best times to post
analyze_post_audience(post_urn) - Audience demographics from commenters
analyze_hashtag_performance(profile_id, post_limit) - Hashtag effectiveness
generate_engagement_report(profile_id, post_limit) - Comprehensive engagement report
get_rate_limit_status() - API rate limit status
get_cache_stats() - Cache performance statistics

Environment Variables

Variable	Default	Description
`LINKEDIN_API_ENABLED`	`false`	Enable the LinkedIn API client
`LOG_LEVEL`	`INFO`	Logging level (DEBUG, INFO, WARNING, ERROR)
`DATABASE_URL`	`sqlite+aiosqlite:///data/linkedin_mcp.db`	Database connection URL
`FEATURE_BROWSER_FALLBACK`	`true`	Enable Playwright browser automation
`FEATURE_ANALYTICS_TRACKING`	`true`	Enable analytics features
`FEATURE_POST_SCHEDULING`	`true`	Enable post scheduling

Troubleshooting

Ensure LINKEDIN_API_ENABLED is set to "true" (as a string) in Claude Desktop config
Verify data/session_cookies.json exists with valid cookies
Check that cookies haven't expired (re-export from browser if needed)
Verify the cwd path is absolute, not relative

LinkedIn session cookies typically last 1-2 weeks. If you're getting authentication errors:

Log into LinkedIn in your browser
Re-export the li_at and JSESSIONID cookies
Update data/session_cookies.json
Restart Claude Desktop

# macOS tail -f ~/Library/Logs/Claude/mcp-server-linkedin.log # Windows (PowerShell) Get-Content -Path "$env:APPDATA\Claude\logs\mcp-server-linkedin.log" -Wait # Linux tail -f ~/.config/Claude/logs/mcp-server-linkedin.log

Architecture

linkedin-mcp/ ├── src/linkedin_mcp/ │ ├── config/ # Settings and constants │ ├── core/ # Context, exceptions, logging, lifespan │ ├── db/ # SQLAlchemy models and repositories │ ├── services/ │ │ ├── linkedin/ # LinkedIn API wrapper │ │ ├── browser/ # Playwright automation │ │ ├── scheduler/ # APScheduler integration │ │ └── analytics/ # Analytics processing │ ├── tools/ # MCP tool definitions │ ├── resources/ # MCP resource definitions │ ├── prompts/ # MCP prompt templates │ ├── server.py # FastMCP server │ └── main.py # Entry point ├── scripts/ # Utility scripts ├── tests/ # Test suite └── data/ # Runtime data (gitignored)

Security & Responsible Use

Important: This server uses the unofficial LinkedIn API which accesses LinkedIn's internal Voyager API.

Use a secondary LinkedIn account for testing
Respect rate limits (~900 requests/hour)
Don't spam or automate engagement excessively
Your account may be restricted if LinkedIn detects automation
Never commit your

Development

# Run tests pytest tests/ -v --cov=linkedin_mcp # Linting ruff check src/ && ruff format src/ # Type checking mypy src/linkedin_mcp # Run locally uv run linkedin-mcp

License

MIT License - see LICENSE for details.

Acknowledgments

tomquirk/linkedin-api - Unofficial LinkedIn API
FastMCP - MCP SDK for Python
Model Context Protocol - AI tool protocol