@fastmcp-me/fetchserp-mcp-server-node

FetchSERP MCP Server

A Model Context Protocol (MCP) server that exposes the FetchSERP API for SEO, SERP analysis, web scraping, and keyword research.

Features

This MCP server provides access to all FetchSERP API endpoints:

SEO & Analysis

• Domain Analysis: Get backlinks, domain info (DNS, WHOIS, SSL, tech stack)
• Keyword Research: Search volume, suggestions, long-tail keyword generation
• SEO Analysis: Comprehensive webpage SEO analysis
• AI Analysis: AI-powered webpage analysis with custom prompts
• Moz Integration: Domain authority and Moz metrics

SERP & Search

• Search Results: Get SERP results from Google, Bing, Yahoo, DuckDuckGo
• AI Overview: Google's AI overview with JavaScript rendering
• Enhanced Results: SERP with HTML or text content
• Ranking Check: Domain ranking for specific keywords
• Indexation Check: Verify if pages are indexed

Web Scraping

• Basic Scraping: Scrape webpages without JavaScript
• JS Scraping: Execute custom JavaScript on pages
• Proxy Scraping: Scrape with country-specific proxies
• Domain Scraping: Scrape multiple pages from a domain

User Management

• Account Info: Check API credits and user information

Installation

No installation required! This MCP server runs directly from GitHub using npx.

Get your FetchSERP API token: Sign up at https://www.fetchserp.com to get your API token. New users get 250 free credits to get started!

Usage

Transport Modes

This MCP server supports two transport modes:

npx mode (Option 1):

• ✅ Zero installation required
• ✅ Always gets latest version from GitHub
• ✅ Perfect for individual users
• ✅ Runs locally with Claude Desktop

HTTP mode (Option 2):

• ✅ Remote deployment capability
• ✅ Multiple clients can connect
• ✅ Better for enterprise/team environments
• ✅ Centralized server management
• ✅ Single API key authentication (FetchSERP token)
• ✅ Scalable architecture

Configuration

Option 1: Using npx (Local/Remote GitHub) Add this server to your MCP client configuration. For example, in Claude Desktop using github registry :

{
  "mcpServers": {
    "fetchserp": {
      "command": "npx",
      "args": [
        "github:fetchSERP/fetchserp-mcp-server-node"
      ],
      "env": {
        "FETCHSERP_API_TOKEN": "your_fetchserp_api_token_here"
      }
    }
  }
}

or using npm registry

{
  "mcpServers": {
    "fetchserp": {
      "command": "npx",
      "args": ["fetchserp-mcp-server"],
      "env": {
        "FETCHSERP_API_TOKEN": "your_fetchserp_api_token_here"
      }
    }
  }
}

Option 2: Claude API with MCP Server For programmatic usage with Claude's API and your deployed MCP server:

const claudeRequest = {
  model: "claude-sonnet-4-20250514",
  max_tokens: 1024,
  messages: [
    {
      role: "user", 
      content: question
    }
  ],
  // MCP Server Configuration
  mcp_servers: [
    {
      type: "url",
      url: "https://mcp.fetchserp.com/sse",
      name: "fetchserp",
      authorization_token: FETCHSERP_API_TOKEN,
      tool_configuration: {
        enabled: true
      }
    }
  ]
};

const response = await httpRequest('https://api.anthropic.com/v1/messages', {
  method: 'POST',
  headers: {
    'x-api-key': CLAUDE_API_KEY,
    'anthropic-version': '2023-06-01',
    'anthropic-beta': 'mcp-client-2025-04-04',
    'content-type': 'application/json'
  }
}, JSON.stringify(claudeRequest));

Option 3: OpenAI API with MCP Server For programmatic usage with OpenAI's API and your deployed MCP server:

const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });

const res = await openai.responses.create({
  model: "gpt-4.1",
  tools: [
    {
      type: "mcp",
      server_label: "fetchserp",
      server_url: "https://mcp.fetchserp.com/sse",
      headers: {
        Authorization: `Bearer ${FETCHSERP_API_TOKEN}`
      }
    }
  ],
  input: question
});

console.log(res.choices[0].message);

Option 4: Docker Use the pre-built Docker image from GitHub Container Registry for containerized deployment:

{
  "mcpServers": {
    "fetchserp": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "FETCHSERP_API_TOKEN",
        "ghcr.io/fetchserp/fetchserp-mcp-server-node:latest"
      ],
      "env": {
        "FETCHSERP_API_TOKEN": "your_fetchserp_api_token_here"
      }
    }
  }
}

Docker Features:

• ✅ Containerized deployment
• ✅ Cross-platform compatibility (ARM64 & AMD64)
• ✅ Isolated environment
• ✅ Easy scaling and deployment
• ✅ Automated builds from GitHub

Manual Docker Usage:

# Pull the latest image
docker pull ghcr.io/fetchserp/fetchserp-mcp-server-node:latest

# Run with environment variable
docker run -i --rm \
  -e FETCHSERP_API_TOKEN="your_token_here" \
  ghcr.io/fetchserp/fetchserp-mcp-server-node:latest

# Or run in HTTP mode on port 8000
docker run -p 8000:8000 \
  -e FETCHSERP_API_TOKEN="your_token_here" \
  -e MCP_HTTP_MODE=true \
  ghcr.io/fetchserp/fetchserp-mcp-server-node:latest

Available Tools

Domain & SEO Analysis

get_backlinks

Get backlinks for a domain

• domain (required): Target domain
• search_engine: google, bing, yahoo, duckduckgo (default: google)
• country: Country code (default: us)
• pages_number: Pages to search 1-30 (default: 15)

get_domain_info

Get comprehensive domain information

• domain (required): Target domain

get_domain_emails

Extract emails from a domain

• domain (required): Target domain
• search_engine: Search engine (default: google)
• country: Country code (default: us)
• pages_number: Pages to search 1-30 (default: 1)

get_playwright_mcp

Use GPT-4.1 to remote control a browser via a Playwright MCP server

• prompt (required): The prompt to use for remote control of the browser

This endpoint uses GPT-4.1 to remote control a browser via a Playwright MCP server.

get_webpage_seo_analysis

Comprehensive SEO analysis of a webpage

• url (required): URL to analyze

get_webpage_ai_analysis

AI-powered webpage analysis

• url (required): URL to analyze
• prompt (required): Analysis prompt

generate_wordpress_content

Generate WordPress content using AI with customizable prompts and models

• user_prompt (required): The user prompt
• system_prompt (required): The system prompt
• ai_model: The AI model (default: gpt-4.1-nano)

Generates SEO-optimized WordPress content including title and content (800-1500 words) with keyword targeting in the first 100 words.

generate_social_content

Generate social media content using AI with customizable prompts and models

• user_prompt (required): The user prompt
• system_prompt (required): The system prompt
• ai_model: The AI model (default: gpt-4.1-nano)

Generates engaging social media content optimized for various platforms and audiences.

get_moz_analysis

Get Moz domain authority and metrics

• domain (required): Target domain

Keyword Research

get_keywords_search_volume

Get search volume for keywords

• keywords (required): Array of keywords
• country: Country code

get_keywords_suggestions

Get keyword suggestions

• url: URL to analyze (optional if keywords provided)
• keywords: Array of seed keywords (optional if url provided)
• country: Country code

get_long_tail_keywords

Generate long-tail keywords

• keyword (required): Seed keyword
• search_intent: informational, commercial, transactional, navigational (default: informational)
• count: Number to generate 1-500 (default: 10)

SERP & Search

get_serp_results

Get search engine results

• query (required): Search query
• search_engine: google, bing, yahoo, duckduckgo (default: google)
• country: Country code (default: us)
• pages_number: Pages to search 1-30 (default: 1)

get_serp_html

Get SERP results with HTML content

• Same parameters as get_serp_results

get_serp_text

Get SERP results with text content

• Same parameters as get_serp_results

get_serp_ai_mode

Get SERP with AI Overview and AI Mode response

• query (required): Search query
• country: Country code (default: us)

Returns AI overview and AI mode response for the query. Less reliable than the 2-step process but returns results in under 30 seconds.

check_page_indexation

Check if domain is indexed for keyword

• domain (required): Target domain
• keyword (required): Search keyword

get_domain_ranking

Get domain ranking for keyword

• keyword (required): Search keyword
• domain (required): Target domain
• search_engine: Search engine (default: google)
• country: Country code (default: us)
• pages_number: Pages to search 1-30 (default: 10)

Web Scraping

scrape_webpage

Scrape webpage without JavaScript

• url (required): URL to scrape

scrape_domain

Scrape multiple pages from domain

• domain (required): Target domain
• max_pages: Maximum pages to scrape, up to 200 (default: 10)

scrape_webpage_js

Scrape webpage with custom JavaScript

• url (required): URL to scrape
• js_script (required): JavaScript code to execute

scrape_webpage_js_proxy

Scrape webpage with JavaScript and proxy

• url (required): URL to scrape
• country (required): Proxy country
• js_script (required): JavaScript code to execute

User Management

get_user_info

Get user information and API credits

• No parameters required

API Token

You need a FetchSERP API token to use this server.

Getting your API token:

• Sign up at https://www.fetchserp.com
• New users automatically receive 250 free credits to get started
• Your API token will be available in your dashboard

Set the token as an environment variable:

export FETCHSERP_API_TOKEN="your_token_here"

Error Handling

The server includes comprehensive error handling:

• Missing API token validation
• API response error handling
• Input validation
• Proper MCP error responses

Docker deploy

docker build --platform=linux/amd64 -t olivier86/fetchserp-mcp-server-node:latest --push .
docker build --platform=linux/amd64 -t ghcr.io/fetchserp/mcp-server-node:latest --push .

docker run -p 8000:8000 olivier86/fetchserp-mcp-server-node:latest

To start tunneling

nohup ngrok http 8000 --domain guinea-dominant-jolly.ngrok-free.app > /var/log/ngrok.log 2>&1 &

npm login npm publish --access public