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bartest5

MCP Server for LinkedIn

by bartest5

Search People

search_people
Read-only

Search LinkedIn for people by keywords, location, connection degree, or current company to find relevant profiles.

Instructions

Search for people on LinkedIn.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
networkNoOptional connection-degree filter. Each element is one of "F" (1st-degree), "S" (2nd-degree), "O" (3rd-degree and beyond). Example: ["F"] to only return 1st-degree connections.
keywordsYesSearch keywords (e.g., "software engineer", "recruiter at Google")
locationNoOptional location filter (e.g., "New York", "Remote")
current_companyNoOptional current-employer filter. LinkedIn's currentCompany facet only filters on the numeric company URN id (e.g. "1115" for SAP); plain company names are accepted by the URL but ignored by LinkedIn and return the unfiltered result set. Look up a company's URN via get_company_profile -- it is exposed under references["about"]. For company-wide employee demographics (location/education/function breakdown) plus a slug-based lookup, use get_company_employees instead.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations provide readOnlyHint=true and openWorldHint=true, which already indicate a safe read operation and potentially incomplete results. The description adds no additional behavioral context such as pagination, rate limits, or authentication requirements. It does not contradict the annotations, and the simple statement is consistent with the expected behavior.

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: 'Search for people on LinkedIn.' It is front-loaded with the verb and resource, contains no unnecessary words, and perfectly communicates the tool's core purpose.

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

Completeness5/5

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

The tool includes a comprehensive input schema with parameter descriptions and an output schema, so the description does not need to explain return values or parameter syntax. The description is complete for a fully specified search tool, and the annotations cover safety and open-world semantics.

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?

Schema description coverage is 100%, and each parameter has a detailed description in the input schema. The tool description adds no parameter-specific meaning, so it neither enhances nor detracts from the schema. Given the high coverage, a score of 3 is appropriate.

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 function: 'Search for people on LinkedIn.' It uses a specific verb ('search') and resource ('people'), and distinguishes from sibling tools like search_companies and search_jobs by indicating the entity type.

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 provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions or alternative tools, leaving the agent to infer from the tool name and sibling list. The only alternative reference is in the current_company parameter description, but not in the main description.

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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