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Ritesh-sudo

Job Search MCP Server

by Ritesh-sudo

search_specific_job_site

Search for AI/ML internships and entry-level positions on LinkedIn, Indeed, Glassdoor, ZipRecruiter, or Monster. Filter results by location and Python proficiency to find relevant job opportunities with application URLs.

Instructions

Search for jobs on a specific job site

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesJob site to search
locationNoJob locationRemote
maxResultsNoMaximum number of results to return

Implementation Reference

  • The handler function for the 'search_specific_job_site' tool. It parses arguments, builds a JobFilter for AI/ML entry-level jobs requiring Python, calls jobSearchService.searchSite, and returns the results as a JSON string in the MCP response format.
    private async searchSpecificJobSite(args: any) {
      const { site, location = 'Remote', maxResults = 25 } = args;
    
      const filter: JobFilter = {
        location,
        maxResults,
        includeInternships: true,
        includeFullTime: true,
        keywords: [],
        experienceLevel: 'entry',
        requiredSkills: ['python'],
        jobTypes: ['ai', 'ml', 'machine learning', 'artificial intelligence', 'data science']
      };
    
      const results = await this.jobSearchService.searchSite(site, filter);
      
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(results, null, 2)
          }
        ]
      };
    }
  • Input schema defining parameters for the tool: site (required, enum of job sites), location, maxResults.
    inputSchema: {
      type: 'object',
      properties: {
        site: {
          type: 'string',
          enum: ['linkedin', 'indeed', 'glassdoor', 'ziprecruiter', 'monster'],
          description: 'Job site to search'
        },
        location: {
          type: 'string',
          description: 'Job location',
          default: 'Remote'
        },
        maxResults: {
          type: 'number',
          description: 'Maximum number of results to return',
          default: 25
        }
      },
      required: ['site']
    }
  • src/index.ts:107-110 (registration)
    Registration in the tool dispatch switch statement within the CallToolRequestSchema handler.
    case 'search_ai_ml_jobs':
      return await this.searchAIMLJobs(args);
    case 'search_specific_job_site':
      return await this.searchSpecificJobSite(args);
  • src/index.ts:73-97 (registration)
    Tool registration in the ListToolsRequestSchema response, including name, description, and input schema.
    {
      name: 'search_specific_job_site',
      description: 'Search for jobs on a specific job site',
      inputSchema: {
        type: 'object',
        properties: {
          site: {
            type: 'string',
            enum: ['linkedin', 'indeed', 'glassdoor', 'ziprecruiter', 'monster'],
            description: 'Job site to search'
          },
          location: {
            type: 'string',
            description: 'Job location',
            default: 'Remote'
          },
          maxResults: {
            type: 'number',
            description: 'Maximum number of results to return',
            default: 25
          }
        },
        required: ['site']
      }
    }
  • Core helper method called by the handler. Retrieves the site-specific scraper, calls its search method with the filter, applies post-search filtering, and returns structured results or error.
    async searchSite(site: string, filter: JobFilter): Promise<JobSearchResult> {
      const startTime = Date.now();
      const scraper = this.scrapers.get(site.toLowerCase());
      
      if (!scraper) {
        throw new Error(`Unsupported job site: ${site}`);
      }
    
      try {
        const jobs = await scraper.search(filter);
        const filteredJobs = this.filterJobs(jobs, filter);
        
        return {
          site,
          jobs: filteredJobs,
          totalFound: filteredJobs.length,
          searchTime: Date.now() - startTime
        };
      } catch (error) {
        return {
          site,
          jobs: [],
          totalFound: 0,
          searchTime: Date.now() - startTime,
          error: error instanceof Error ? error.message : 'Unknown error'
        };
      }
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the action is a search but doesn't disclose behavioral traits like whether it's read-only, what permissions are needed, rate limits, or what the output looks like (e.g., list of jobs with details). This leaves significant gaps for a tool with parameters.

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, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the core purpose without unnecessary elaboration.

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?

Given no annotations, no output schema, and a tool with 3 parameters, the description is incomplete. It doesn't explain what the search returns (e.g., job listings, error handling) or behavioral aspects, making it inadequate for proper agent usage despite good conciseness.

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 schema already documents all parameters (site, location, maxResults) with descriptions and defaults. The description adds no additional meaning beyond implying a search context, which is minimal value. Baseline 3 is appropriate when schema does the heavy lifting.

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 action ('Search for jobs') and resource ('on a specific job site'), making the purpose understandable. However, it doesn't differentiate from the sibling tool 'search_ai_ml_jobs' (which presumably searches for AI/ML jobs rather than by site), so it lacks explicit sibling distinction.

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 like 'search_ai_ml_jobs'. It mentions 'specific job site' but doesn't explain when to choose this over other search methods or what contexts it's best suited for.

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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