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fetchSERP

FetchSERP MCP Server

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by fetchSERP

get_long_tail_keywords

Generate long-tail keywords from a seed keyword to enhance SEO targeting. Specify search intent and quantity for precise results.

Instructions

Generate long-tail keywords for a given keyword

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoThe number of long-tail keywords to generate (1-500). Default: 10
keywordYesThe seed keyword to generate long-tail keywords from
search_intentNoThe search intent (informational, commercial, transactional, navigational). Default: informationalinformational

Implementation Reference

  • index.js:157-182 (registration)
    Registration of the get_long_tail_keywords tool in the ListTools response, including name, description, and inputSchema definition.
    {
      name: 'get_long_tail_keywords',
      description: 'Generate long-tail keywords for a given keyword',
      inputSchema: {
        type: 'object',
        properties: {
          keyword: {
            type: 'string',
            description: 'The seed keyword to generate long-tail keywords from',
          },
          search_intent: {
            type: 'string',
            description: 'The search intent (informational, commercial, transactional, navigational). Default: informational',
            default: 'informational',
          },
          count: {
            type: 'integer',
            description: 'The number of long-tail keywords to generate (1-500). Default: 10',
            default: 10,
            minimum: 1,
            maximum: 500,
          },
        },
        required: ['keyword'],
      },
    },
  • Handler implementation for get_long_tail_keywords tool. Proxies the tool call to the FetchSERP API endpoint /api/v1/long_tail_keywords_generator using a GET request with the provided arguments.
    case 'get_long_tail_keywords':
      return await this.makeRequest('/api/v1/long_tail_keywords_generator', 'GET', args, null, token);
  • Shared helper method makeRequest used by the tool 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'generate' implies creation, it doesn't specify whether this is a read-only operation, if it requires API calls or external services, what the output format looks like, or any rate limits or authentication needs. The description is too minimal for a tool that likely involves algorithmic generation.

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 no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place, though this conciseness comes at the cost of detail.

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 the complexity of keyword generation and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'long-tail keywords' means in this context, how they're generated, the output format, or any behavioral traits. For a tool with 3 parameters and no structured output information, more context 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?

The description mentions 'for a given keyword', which hints at the 'keyword' parameter, but adds no semantic context beyond what's already in the schema. With 100% schema description coverage, the baseline is 3, as the schema fully documents parameters like 'count' and 'search_intent' with their constraints and defaults.

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 verb 'generate' and the resource 'long-tail keywords for a given keyword', making the purpose understandable. However, it doesn't distinguish this tool from potential sibling tools like 'get_keywords_suggestions' or 'get_keywords_search_volume', which might also involve keyword generation or analysis.

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. With multiple sibling tools related to keywords, SEO, and content generation, there's no indication of specific use cases, prerequisites, or comparisons to tools like 'get_keywords_suggestions' or 'generate_social_content'.

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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