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fetchSERP

FetchSERP MCP Server

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by fetchSERP

get_domain_emails

Extract email addresses from a specified domain using selected search engines and country filters for precise data retrieval.

Instructions

Retrieve emails from a given domain

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoThe country to search from. Default: usus
domainYesThe domain to search emails from
pages_numberNoThe number of pages to search (1-30). Default: 1
search_engineNoThe search engine to use (google, bing, yahoo, duckduckgo). Default: googlegoogle

Implementation Reference

  • Handler for the get_domain_emails tool. It calls the makeRequest helper to fetch emails from the FetchSERP API endpoint '/api/v1/domain_emails' using the provided arguments.
    case 'get_domain_emails':
      return await this.makeRequest('/api/v1/domain_emails', 'GET', args, null, token);
  • Input schema for the get_domain_emails tool, defining parameters like domain (required), search_engine, country, and pages_number.
    inputSchema: {
      type: 'object',
      properties: {
        domain: {
          type: 'string',
          description: 'The domain to search emails from',
        },
        search_engine: {
          type: 'string',
          description: 'The search engine to use (google, bing, yahoo, duckduckgo). Default: google',
          default: 'google',
        },
        country: {
          type: 'string',
          description: 'The country to search from. Default: us',
          default: 'us',
        },
        pages_number: {
          type: 'integer',
          description: 'The number of pages to search (1-30). Default: 1',
          default: 1,
          minimum: 1,
          maximum: 30,
        },
      },
      required: ['domain'],
    },
  • index.js:71-101 (registration)
    Registration of the get_domain_emails tool in the ListTools response, including name, description, and input schema.
    {
      name: 'get_domain_emails',
      description: 'Retrieve emails from a given domain',
      inputSchema: {
        type: 'object',
        properties: {
          domain: {
            type: 'string',
            description: 'The domain to search emails from',
          },
          search_engine: {
            type: 'string',
            description: 'The search engine to use (google, bing, yahoo, duckduckgo). Default: google',
            default: 'google',
          },
          country: {
            type: 'string',
            description: 'The country to search from. Default: us',
            default: 'us',
          },
          pages_number: {
            type: 'integer',
            description: 'The number of pages to search (1-30). Default: 1',
            default: 1,
            minimum: 1,
            maximum: 30,
          },
        },
        required: ['domain'],
      },
    },
  • Shared helper function makeRequest used by the get_domain_emails handler to perform authenticated HTTP requests to the FetchSERP API.
    async makeRequest(endpoint, method = 'GET', params = {}, body = null, token = null) {
      const fetchserpToken = token || process.env.FETCHSERP_API_TOKEN;
      
      if (!fetchserpToken) {
        throw new McpError(
          ErrorCode.InvalidRequest,
          'FETCHSERP_API_TOKEN is required'
        );
      }
    
      const url = new URL(`${API_BASE_URL}${endpoint}`);
      
      // Add query parameters for GET requests
      if (method === 'GET' && Object.keys(params).length > 0) {
        Object.entries(params).forEach(([key, value]) => {
          if (value !== undefined && value !== null) {
            if (Array.isArray(value)) {
              value.forEach(v => url.searchParams.append(`${key}[]`, v));
            } else {
              url.searchParams.append(key, value.toString());
            }
          }
        });
      }
    
      const fetchOptions = {
        method,
        headers: {
          'Authorization': `Bearer ${fetchserpToken}`,
          'Content-Type': 'application/json',
        },
      };
    
      if (body && method !== 'GET') {
        fetchOptions.body = JSON.stringify(body);
      }
    
      const response = await fetch(url.toString(), fetchOptions);
      
      if (!response.ok) {
        const errorText = await response.text();
        throw new McpError(
          ErrorCode.InternalError,
          `API request failed: ${response.status} ${response.statusText} - ${errorText}`
        );
      }
    
      return await response.json();
    }
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool retrieves emails but doesn't explain how (e.g., via search engines as indicated in the schema), what format the results come in, whether there are rate limits, authentication requirements, or potential privacy implications. The description is too vague about the actual behavior.

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, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action 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?

For a tool with 4 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns (email addresses? email content? metadata?), how results are structured, or any behavioral constraints. The agent would be left guessing about important operational aspects.

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 fully documents all parameters. The description adds no additional parameter information beyond what's in the schema, meeting the baseline expectation but not providing extra value.

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 ('Retrieve emails') and target resource ('from a given domain'), making the purpose understandable. However, it doesn't differentiate this tool from potential sibling email-related tools (none are listed among siblings, but the description doesn't explicitly confirm this uniqueness).

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. It doesn't mention any prerequisites, limitations, or scenarios where other tools might be more appropriate, leaving the agent to infer usage from the tool name alone.

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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