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BACH-AI-Tools

Fresh Linkedin Profile Data MCP Server

Get Search Results

get_search_results

Retrieve paginated LinkedIn search results using a request ID and page number to access profile, company, or job data from the Fresh Linkedin Profile Data API.

Instructions

Get search results. Please make sure the search is \

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYesExample value: 1
request_idYesExample value: dd1b29063de8927b31fa523d36432b61

Schema Changelog

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

  1. First observedv2.0.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It only says 'Get search results,' implying a read operation, but it does not explain pagination behavior, whether this depends on a prior async search, what happens with stale or missing request IDs, or what response to expect.

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

Conciseness2/5

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

The description is very short, which is good, but it is also malformed and incomplete, ending with an unfinished quoted phrase. Brevity is not valuable when the content fails to communicate a complete instruction.

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

Completeness1/5

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

This tool has no annotations and no output schema, so a complete description is essential. The description does not explain the search lifecycle, the meaning of request_id, pagination semantics, or any error conditions. It is far too incomplete for an agent to invoke correctly.

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

Parameters2/5

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

The input schema properties have descriptions, but they are only example values ('Example value: 1', 'Example value: dd1b...'), not semantic explanations. The tool description adds nothing about how request_id or page should be used, so the agent is left to guess their roles.

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 states a clear verb and resource: 'Get search results.' This is reasonably specific, but it does not differentiate get_search_results from the many sibling search-related tools such as check_search_status or search_leads, so it falls short of a top score.

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?

No practical guidance is given about when to use this tool versus alternatives. The sentence 'Please make sure the search is "' is an incomplete fragment and provides no usable direction about prerequisites, timing, or exclusions.

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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