MCP-LinkedIn
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LINKEDIN_COOKIE | Yes | Your LinkedIn session cookie (li_at value) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_person_profileA | Get a specific person's LinkedIn profile. Args: linkedin_username (str): LinkedIn username (e.g., "stickerdaniel", "anistji") Returns: Dict[str, Any]: Structured data from the person's profile |
| get_company_profileA | Get a specific company's LinkedIn profile. Args: company_name (str): LinkedIn company name (e.g., "docker", "anthropic", "microsoft") get_employees (bool): Whether to scrape the company's employees (slower) Returns: Dict[str, Any]: Structured data from the company's profile |
| get_job_detailsA | Get job details for a specific job posting on LinkedIn Args: job_id (str): LinkedIn job ID (e.g., "4252026496", "3856789012") Returns: Dict[str, Any]: Structured job data including title, company, location, posting date, application count, and job description (may be empty if content is protected) |
| search_jobsB | Search for jobs on LinkedIn using a search term. Args: search_term (str): Search term to use for the job search. Returns: List[Dict[str, Any]]: List of job search results |
| get_recommended_jobsB | Get your personalized recommended jobs from LinkedIn Returns: List[Dict[str, Any]]: List of recommended jobs |
| close_sessionA | Close the current browser session and clean up resources. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose with no overlap: close_session handles session management, get_company_profile and get_person_profile target different entity types, while get_job_details, get_recommended_jobs, and search_jobs cover different job-related operations. The descriptions clearly differentiate between retrieving specific entities versus searching/recommending.
All tools follow a consistent verb_noun naming pattern: close_session, get_company_profile, get_job_details, get_person_profile, get_recommended_jobs, and search_jobs. The pattern is uniform throughout with 'get_' or action verbs followed by descriptive nouns, making the set predictable and readable.
Six tools is a reasonable count for a LinkedIn-focused server, covering core operations like profile retrieval, job search, and session management. It's slightly lean but well-scoped; minor additions like update operations or more entity types could enhance it without being necessary.
The toolset covers key read operations for profiles and jobs, but lacks update, create, or delete capabilities typical in social media contexts (e.g., posting updates, sending messages). While agents can retrieve data, they cannot interact or modify content, which limits workflow completeness for a full LinkedIn integration.