LinkBridge MCP

Search People

search_people

Read-only

Find people on LinkedIn using keywords and optional filters for connection degree, location, or current company to identify prospects and contacts.

Instructions

Search for people on LinkedIn.

Input Schema

Name	Required	Description
`network`	No	Optional 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. A single token ("F") or a comma-separated string ("F,S") is also accepted, for clients that cannot transmit an array.
`keywords`	Yes	Search keywords (e.g., "software engineer", "recruiter at Google")
`location`	No	Optional location filter, as LinkedIn's numeric geo URN id (e.g., "103644278" for the United States). Plain-text place names are silently ignored by LinkedIn and return unfiltered results, so they are refused here. The id is the geoUrn value in the URL of a LinkedIn people search filtered to that place; without one, put the place in keywords instead.
`current_company`	No	Optional 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

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv4.29.0Nov 5, 2026

TDQS

C2.9/5.0

Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe, open-world read. The description adds nothing beyond that: no mention of result caps, pagination behavior, throttling risk, or that LinkedIn silently ignores plain-text location and company filters. That filter-failure behavior is detailed in the schema, but the description itself contributes no behavioral context.

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

Conciseness4/5

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

A single sentence with no wasted words, front-loaded with the verb and resource. It is efficient but under-specified; concision here comes at the cost of useful detail rather than from careful editing.

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 tool has four parameters, full schema coverage, an output schema, and read-only annotations, so much of the burden is already carried by structured fields. Still, a search tool with filters and an output schema deserves at least a note on result shape or filtering caveats. The description supplies none of that, leaving it minimally adequate for its complexity.

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%, so the baseline is 3. The schema already explains the network tokens (F/S/O), the numeric geo URN for location, and the company URN lookup path in detail. The description repeats none of this and adds no meaning 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 states a specific verb and resource: 'Search for people on LinkedIn.' This distinguishes it from search_companies, search_jobs, and search_posts by resource even though those siblings are never named. It stops short of the sibling-differentiation required for a 5.

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 use this tool rather than alternatives such as get_person_profile, get_company_employees, or get_sidebar_profiles. No prerequisites, no mention of connection limitations, and no note on when a keyword search is the right approach instead of a direct profile lookup.

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