linkedin-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| linkedin_get_profileA | Get the authenticated user's LinkedIn profile information including name, email, and profile picture. |
| linkedin_create_postA | Create a text post on LinkedIn. Supports different visibility options: PUBLIC (everyone), CONNECTIONS (1st degree connections only), or LOGGED_IN (LinkedIn members only). |
| linkedin_create_article_postA | Create a LinkedIn post with an article/link. Great for sharing blog posts, news articles, or any web content with your network. |
| linkedin_get_postsA | Get the authenticated user's recent LinkedIn posts. Note: This may require additional API permissions. |
| linkedin_delete_postA | Delete a LinkedIn post by its ID. |
| linkedin_get_connections_countA | Get the number of LinkedIn connections. Note: This may require additional API permissions. |
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 targets a distinct operation: creating article vs text posts, deleting posts, retrieving posts, profile, and connections count. No overlap in functionality.
All tools follow a consistent 'linkedin_verb_noun' pattern (e.g., linkedin_create_post, linkedin_get_profile), making the naming predictable and clear.
With 6 tools covering posting, reading, and profile operations, the count is well-scoped for a focused LinkedIn server, not too many or too few.
Covers core post creation, deletion, and retrieval, but lacks update post and more detailed connection data, leaving notable gaps for a complete LinkedIn interaction surface.