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felipfr

LinkedIn MCP Server

by felipfr

search_people

Find LinkedIn professionals by applying filters for name, company, title, location, industry, and school.

Instructions

Search LinkedIn professionals with advanced filters and criteria

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsNoSearch keywords
firstNameNoFirst name
lastNameNoLast name
companyNameNoCurrent company name
titleNoJob title
locationNoLocation
industryNoIndustry
schoolNoSchool/university

Implementation Reference

  • The core handler that executes the LinkedIn API search for people. Builds query parameters from keywords, location, currentCompany, and industries, then makes a GET request to the LinkedIn API.
    public async searchPeople(params: SearchPeopleParams): Promise<SearchPeopleResult> {
      const queryParams = new URLSearchParams()
    
      const paramMapping: Record<string, string | undefined> = {
        keywords: params.keywords,
        location: params.location
      }
    
      Object.entries(paramMapping)
        .filter(([_, value]) => value !== undefined)
        .forEach(([key, value]) => queryParams.append(key, value as string))
    
      this.appendArrayParams(queryParams, {
        'current-company': params.currentCompany,
        'facet-industry': params.industries
      })
    
      return this.makeRequest<SearchPeopleResult>('get', `/search/people?${queryParams.toString()}`)
  • Zod validation schema defining the input parameters for search-people: keywords (string), location (string), currentCompany (array of strings), and industries (array of strings).
    searchPeople: {
      currentCompany: z.array(z.string()).optional().describe('Filter by current company'),
      industries: z.array(z.string()).optional().describe('Filter by industries'),
      keywords: z.string().optional().describe('Keywords to search for LinkedIn Profiles'),
      location: z.string().optional().describe('Filter by location')
    },
  • src/server.ts:68-82 (registration)
    Registers the 'search-people' tool with the MCP server, linking the schema (linkedinApiSchemas.searchPeople) to the handler that calls clientService.searchPeople(params).
    this.server.tool(
      'search-people',
      'Search for LinkedIn profiles based on various criteria',
      linkedinApiSchemas.searchPeople,
      async (params) => {
        this.logger.info('Executing LinkedIn People Search', { keywords: params.keywords })
        try {
          const results = await this.clientService.searchPeople(params)
          return this.createResourceResponse(results)
        } catch (error) {
          this.logger.error('LinkedIn People Search Failed', error)
          throw error
        }
      }
    )
  • TypeScript type definition for SearchPeopleParams used as input to the searchPeople handler.
    export interface SearchPeopleParams {
      keywords?: string
      location?: string
      currentCompany?: string[]
      industries?: string[]
    }
  • TypeScript type definition for SearchPeopleResult returned by the searchPeople handler.
    export interface SearchPeopleResult {
      people: LinkedInProfile[]
      paging: {
        count: number
        start: number
        total: number
      }
    }
Behavior2/5

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

No annotations exist, and the description provides no behavioral details such as authentication requirements, rate limits, or what happens with no results. Only the basic search action is mentioned.

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?

The description is a single concise sentence that is front-loaded. It is efficiently written but could benefit from more specificity.

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

Completeness2/5

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

Despite 100% schema coverage, the description omits important context such as expected output format, pagination, or result limits. Given 8 parameters and no output schema, more completeness is needed.

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 baseline is 3. The description adds no extra meaning beyond the schema's parameter descriptions, which are minimal (e.g., 'Search keywords').

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 clearly states the tool searches LinkedIn professionals and mentions advanced filters, distinguishing it from sibling tools like search_jobs. However, it lacks specific detail on what 'advanced' entails.

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 guidance on when to use this tool versus alternatives like search_jobs or get_profile. No when-not-to-use or prerequisite information provided.

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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