Linkd 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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_for_usersC | Search for users on Linkd using filters like query, school, and match threshold. |
| search_for_companiesC | Search for companies on Linkd using filters like query and match threshold. |
| enrich_linkedinA | Retrieves detailed profile information for a specific LinkedIn URL. Each successful lookup costs 1 credit. |
| retrieve_contactsA | Retrieves email addresses and phone numbers for a LinkedIn profile. Each lookup costs 1 credit. |
| scrape_linkedinA | Retrieves detailed profile data and posts with comments from a LinkedIn profile URL using RapidAPI. Each request costs 2 credits. |
| initiate_deep_researchB | Initiate a deep research job that combines multiple search variations with optional email enrichment. Each result costs 1 credit. |
| check_deep_research_statusC | Check the status of an ongoing deep research job. |
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 7 tools
Most tools have distinct purposes, but 'enrich_linkedin' and 'scrape_linkedin' could be confused as both retrieve detailed profile information. The descriptions clarify that 'scrape_linkedin' includes posts and comments, while 'enrich_linkedin' is more basic, but the overlap in core functionality might cause misselection.
Tool names follow a consistent snake_case pattern with clear verb_noun structures, such as 'check_deep_research_status' and 'search_for_users'. Minor deviations exist, like 'enrich_linkedin' using a verb without an explicit object, but overall the naming is predictable and readable.
With 7 tools, the count is well-scoped for a LinkedIn-focused server, covering key operations like profile retrieval, research, and searches. Each tool appears to earn its place without being excessive or insufficient for the domain.
The toolset provides good coverage for LinkedIn operations, including profile enrichment, contact retrieval, and searches for users and companies. Minor gaps exist, such as no explicit update or delete tools, but these are less critical in a data retrieval context, and agents can likely work around them.