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ChanMeng666

Google Jobs MCP Server

by ChanMeng666

search_jobs

Search for jobs using Google Jobs API with filters for location, date, job type, salary, and language to find relevant employment opportunities.

Instructions

Google Jobs API search tool.

Supported search parameters:

  1. Basic Search: Job title or keywords

  2. Location: City or region

  3. Time Filter: Recently posted jobs

  4. Job Type: Full-time, part-time, contract, internship

  5. Salary Range: Filter by compensation

  6. Geographic Range: Set search radius

  7. Language: Multi-language support

All parameters except 'query' are optional and can be freely combined.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch keywords (Required, e.g., 'software engineer', 'data analyst', 'product manager')
locationNoJob location (Optional, e.g., 'New York', 'London', 'Tokyo')
posted_ageNoPosting date filter (Optional) Options: - "today": Posted today - "3days": Last 3 days - "week": Last week - "month": Last month
employment_typeNoJob type (Optional) Options: - "FULLTIME": Full-time - "PARTTIME": Part-time - "CONTRACTOR": Contractor - "INTERN": Internship - "TEMPORARY": Temporary
salaryNoSalary range (Optional) Format examples: - "$50K+": Above $50,000 - "$100K+": Above $100,000 - "$150K+": Above $150,000
radiusNoSearch radius (Optional) Format examples: - "10mi": Within 10 miles - "20mi": Within 20 miles - "50mi": Within 50 miles
hlNoResult language (Optional) Options: - "en": English - "zh-CN": Chinese - "ja": Japanese - "ko": Koreanen
pageNoPage number (Optional, default: 1) - 10 results per page - Supports pagination
sort_byNoSort order (Optional) Options: - "date": Sort by date - "relevance": Sort by relevance - "salary": Sort by salaryrelevance

Implementation Reference

  • Defines the tool metadata, description, and detailed input schema with parameters, types, descriptions, and defaults for the search_jobs tool.
    const SEARCH_JOBS_TOOL = {
      name: "search_jobs",
      description: `Google Jobs API search tool.
    
    Supported search parameters:
    1. Basic Search: Job title or keywords
    2. Location: City or region
    3. Time Filter: Recently posted jobs
    4. Job Type: Full-time, part-time, contract, internship
    5. Salary Range: Filter by compensation
    6. Geographic Range: Set search radius
    7. Language: Multi-language support
    
    All parameters except 'query' are optional and can be freely combined.`,
      inputSchema: {
        type: "object",
        properties: {
          query: {
            type: "string",
            description: "Search keywords (Required, e.g., 'software engineer', 'data analyst', 'product manager')"
          },
          location: {
            type: "string",
            description: "Job location (Optional, e.g., 'New York', 'London', 'Tokyo')",
            default: ""
          },
          posted_age: {
            type: "string",
            description: `Posting date filter (Optional)
    Options:
    - "today": Posted today
    - "3days": Last 3 days
    - "week": Last week
    - "month": Last month`,
            default: ""
          },
          employment_type: {
            type: "string",
            description: `Job type (Optional)
    Options:
    - "FULLTIME": Full-time
    - "PARTTIME": Part-time
    - "CONTRACTOR": Contractor
    - "INTERN": Internship
    - "TEMPORARY": Temporary`,
            default: ""
          },
          salary: {
            type: "string",
            description: `Salary range (Optional)
    Format examples:
    - "$50K+": Above $50,000
    - "$100K+": Above $100,000
    - "$150K+": Above $150,000`,
            default: ""
          },
          radius: {
            type: "string",
            description: `Search radius (Optional)
    Format examples:
    - "10mi": Within 10 miles
    - "20mi": Within 20 miles
    - "50mi": Within 50 miles`,
            default: ""
          },
          hl: {
            type: "string",
            description: `Result language (Optional)
    Options:
    - "en": English
    - "zh-CN": Chinese
    - "ja": Japanese
    - "ko": Korean`,
            default: "en"
          },
          page: {
            type: "number",
            description: `Page number (Optional, default: 1)
    - 10 results per page
    - Supports pagination`,
            default: 1
          },
          sort_by: {
            type: "string",
            description: `Sort order (Optional)
    Options:
    - "date": Sort by date
    - "relevance": Sort by relevance
    - "salary": Sort by salary`,
            default: "relevance"
          }
        },
        required: ["query"]
      }
    };
  • src/index.ts:448-450 (registration)
    Registers the search_jobs tool object in the MCP server's ListTools request handler.
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [SEARCH_JOBS_TOOL]
    }));
  • MCP CallToolRequestSchema handler that validates the tool name and arguments, calls performJobSearch for search_jobs, handles success/error responses with localized error messages.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      try {
        const { name, arguments: args } = request.params;
        
        if (name !== "search_jobs") {
          throw new Error("Unknown tool");
        }
    
        if (!args || typeof args.query !== "string") {
          throw new Error("Invalid arguments for search_jobs");
        }
    
        const results = await performJobSearch(
          args.query,
          args.location as string | undefined,
          args.posted_age as string | undefined,
          args.employment_type as string | undefined,
          args.salary as string | undefined,
          args.radius as string | undefined,
          args.hl as SupportedLanguage | undefined
        );
    
        return {
          content: [{ type: "text", text: results }],
          isError: false
        };
      } catch (error) {
        const args = request.params.arguments as { query?: string; hl?: SupportedLanguage } | undefined;
        const query = args?.query || "";
        const lang = args?.hl || "en";
        const t = getLocalizedText(lang);
        const suggestions = getSearchSuggestions(error, query, lang);
        
        return {
          content: [{ 
            type: "text", 
            text: `❌ ${t.error}:\n${error instanceof Error ? error.message : String(error)}\n${suggestions}` 
          }],
          isError: true
        };
      }
    });
  • Core handler function for search_jobs: validates params, constructs SerpAPI Google Jobs URL with filters, fetches and parses JSON response, formats output using helper functions.
    async function performJobSearch(
      query: string, 
      location?: string, 
      posted_age?: string,
      employment_type?: string,
      salary?: string,
      radius?: string,
      hl?: SupportedLanguage
    ) {
      // Parameter validation
      const warnings = validateSearchParams({
        query,
        location,
        salary,
        radius
      }, hl);
      
      let output = "";
      if (warnings.length > 0) {
        const t = getLocalizedText(hl);
        output += `⚠️ ${t.warning}:\n`;
        warnings.forEach(warning => {
          output += `• ${warning}\n`;
        });
        output += `\n`;
      }
    
      // Build search URL
      const url = new URL('https://serpapi.com/search');
      url.searchParams.set('engine', 'google_jobs');
      url.searchParams.set('q', query);
      url.searchParams.set('api_key', SERP_API_KEY as string);
      
      // Add basic parameters
      if (location) {
        url.searchParams.set('location', location);
      }
      
      if (posted_age) {
        url.searchParams.set('chips', `date_posted:${posted_age}`);
      }
    
      // Add additional parameters
      if (employment_type) {
        url.searchParams.append('chips', `employment_type:${employment_type}`);
      }
    
      if (salary) {
        url.searchParams.append('chips', `salary:${salary}`);
      }
    
      if (radius) {
        url.searchParams.set('location_distance', radius);
      }
    
      if (hl) {
        url.searchParams.set('hl', hl);
      }
    
      // Make API request
      const response = await fetch(url.toString());
      if (!response.ok) {
        throw new Error(`Serp API error: ${response.status} ${response.statusText}`);
      }
    
      // Process response
      const data = await response.json() as JobSearchResponse;
      return output + formatJobResults(
        data.jobs_results || [], 
        data.search_metadata || {}, 
        data.page || 1,
        hl
      );
    }
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 of behavioral disclosure. It describes the search parameters and their optionality, which is useful, but it doesn't mention rate limits, authentication requirements, error handling, or what the output looks like (e.g., format, pagination details beyond '10 results per page' in the schema). For a tool with 9 parameters and no annotations, this leaves significant gaps in understanding its behavior.

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 appropriately sized and front-loaded, starting with the tool's purpose and followed by a structured list of parameters. Every sentence adds value, with no redundant information. However, the bulleted list could be slightly more concise, and the final sentence about optional parameters is necessary but adds length.

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?

Given the complexity (9 parameters, no output schema, no annotations), the description is partially complete. It covers the search parameters well but lacks details on behavioral aspects like rate limits, authentication, and output format. Without annotations or an output schema, the description should do more to compensate, but it provides a functional overview that is adequate for basic use.

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 schema description coverage is 100%, meaning all parameters are well-documented in the input schema itself. The description adds value by summarizing the supported search parameters in a bulleted list and noting their optionality, but it doesn't provide additional semantic context beyond what the schema already covers (e.g., no examples of combined usage). This meets the baseline for high schema coverage.

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 for jobs using the Google Jobs API with specific search parameters. It provides a verb ('search') and resource ('jobs'), making the purpose immediately understandable. However, since there are no sibling tools mentioned, it doesn't need to differentiate from alternatives, so a 5 is not warranted.

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

Usage Guidelines3/5

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

The description implies usage through the list of supported search parameters and notes that all parameters except 'query' are optional. This provides some context for when to use certain features, but it doesn't offer explicit guidance on when to use this tool versus alternatives (none mentioned) or any prerequisites. The guidance is functional but not strategic.

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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