Skip to main content
Glama

nv_search_people

Search LinkedIn Sales Navigator for people using filters like company, location, industry, and experience. Get matching profiles for lead generation and market research.

Instructions

Allows you to search people in Sales Navigator applying various filtering criteria. (nv.searchPeople action).

Linked API actions are queued into a cloud-browser workflow and may take several minutes. The server returns immediately after starting the workflow with {status: 'pending'|'running', pendingReason, workflowId, operationName, message}. To retrieve the final result, call get_workflow_result with the returned workflowId and operationName — it will long-poll until completion or the request budget elapses, then return either the final result or another in-progress snapshot. Do not retry the original tool while a workflow is still running; that creates duplicate queued work.

A pending workflow carries pendingReason: 'queued' means it is waiting its turn behind other work on the same account and will start within minutes. 'outsideWorkingHours' means the account has configured working hours and the workflow is parked until they reopen — possibly the next working day. In that case get_workflow_result returns immediately instead of polling, message states when the window opens, and you should report that to the user rather than looping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termNoOptional. Keyword or phrase to search.
limitNoOptional. Number of search results to return. Defaults to 25, with a maximum value of 2500.
filterNoOptional. Object that specifies filtering criteria for people. When multiple filter fields are specified, they are combined using AND logic.
Behavior5/5

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

With no annotations provided, the description fully discloses the queued cloud-browser workflow, immediate return with status fields, long-poll behavior, and the semantics of pendingReason values ('queued' vs 'outsideWorkingHours'). It also warns against duplicate queued work from retrying. This is exceptional transparency.

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 longer than typical but every sentence is necessary: purpose, async behavior, retry warning, and pendingReason explanations. It is structured logically, front-loading the core action and then detailing workflow implications, with no filler or redundancy.

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?

Given no output schema and no annotations, the description covers the return contract, workflow lifecycle, retry guidance, and edge cases like working hours. It is a complete usage guide for a complex async tool, leaving little ambiguity for the agent.

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 has 100% description coverage for all parameters, including filter object semantics and enum ranges. The description adds no extra parameter-level detail beyond 'various filtering criteria,' so it meets the baseline 3 for high schema coverage without adding value.

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 states a specific action: 'search people in Sales Navigator applying various filtering criteria.' This clearly distinguishes it from sibling tools like nv_search_companies (search companies) and nv_fetch_person (fetch individual). The resource and verb are explicit.

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

Usage Guidelines4/5

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

The description provides detailed usage guidance for the async workflow, including when to call get_workflow_result and the warning not to retry while a workflow is running. However, it does not explicitly compare against alternative search tools like search_people or state when to choose this vs a non-nv variant, so it lacks exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/zecloud/remote-mcp-linkedin'

If you have feedback or need assistance with the MCP directory API, please join our Discord server