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BACH-AI-Tools

Fresh Linkedin Profile Data MCP Server

Get Extra Profile Data

get_extra_profile_data

Retrieve additional LinkedIn profile fields including languages, top skills, certifications, publications, patents, and awards.

Instructions

Get more profile’s data fields like languages, top skills, certifications, publications, patents, awards

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linkedin_urlYesExample value: https://www.linkedin.com/in/ajjames/

Schema Changelog

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

  1. First observedv2.0.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden, and it does communicate the core read behavior ('Get...') plus the specific data categories returned. It does not disclose potential failure modes (e.g., private profiles), rate limits, authentication, or response shape, which are meaningful gaps for a tool without annotations.

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?

A single, front-loaded sentence communicates the action, target, and examples of returned content with no filler. Every phrase earns its place.

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

Completeness3/5

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

The definition is adequate for a simple one-parameter getter that asks for a linkedin_url and returns a known list of field types. However, without an output schema or annotations, the description does not clarify expected output structure, empty/error behavior, or whether the profile must be public.

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 input schema already documents linkedin_url with 100% coverage and an example value, so the baseline is 3. The description's mention of 'profile's data fields' weakly reinforces that the URL is a profile URL, but adds no syntax or formatting detail beyond the schema.

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

Purpose4/5

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

The description says the tool 'Get more profile’s data fields' and enumerates exact field types (languages, top skills, certifications, publications, patents, awards), making the action and resource clear. It does not explicitly distinguish it from siblings like get_years_of_experience or get_open_profile_status, so it misses full differentiation.

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?

There is no guidance on when to choose this over the many profile-related siblings, nor any exclusions or prerequisites. The phrase 'extra profile data' implies a use case, but the agent is left to infer when this tool is appropriate.

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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