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N-Graves

linkedin-mcp-server

by N-Graves

linkedin_get_me

Retrieves the authenticated LinkedIn member's profile details including ID, name, and email when the access token has the required scope.

Instructions

The authenticated member — id, name and email if the token carries the scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description bears full responsibility for behavioral transparency. It mentions the condition for email retrieval ('if the token carries the scope') but does not disclose potential errors, rate limits, authentication requirements, or any side effects. The read-only nature is implied but not explicitly stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that conveys all essential information without padding. It avoids unnecessary details and is well-structured for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides sufficient context for the tool's expected behavior: it returns the member's id, name, and email (under a scope condition). Since there is no output schema, this explanation of the return content is valuable. It does not cover error cases or output formatting, but for a simple retrieval tool, this is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema coverage is therefore 100% (empty). The description adds no additional meaning beyond the absence of parameters, which is already evident from the empty schema. This meets the baseline but does not exceed it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: retrieving the authenticated member's id, name, and email (with a scope condition). It identifies the specific resource ('me') and the data returned, leaving no ambiguity about what the tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no explicit guidance on when to use this tool versus its siblings (e.g., linkedin_call or linkedin_create_post). While the purpose is self-evident, it does not mention alternatives or situations where another tool would be preferred, so the guidance is only implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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