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SEO AI Assistant

by ccnn2509
GitHub
JavaScript
21
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App SEO AI

Application for SEO automation and AI-powered optimization with Google Ads Keyword Planner integration.

Features

  • Keyword research using Google Ads API
  • SERP analysis
  • Competitor analysis
  • SEO recommendations
  • MCP (Model Context Protocol) integration for AI assistants

Prerequisites

  • Node.js (v14 or higher)
  • npm or yarn
  • Google Ads account with API access
  • Google Cloud Platform project with Google Ads API enabled

Setup

1. Clone the repository

git clone https://github.com/ccnn2509/app-seo-ai.git cd app-seo-ai

2. Install dependencies

npm install

3. Configure environment variables

Copy the example environment file:

cp .env.example .env

Edit the .env file and fill in your Google Ads API credentials:

# Server Configuration PORT=3000 NODE_ENV=development # Google Ads API Configuration GOOGLE_ADS_DEVELOPER_TOKEN=your_developer_token GOOGLE_ADS_CLIENT_ID=your_client_id GOOGLE_ADS_CLIENT_SECRET=your_client_secret GOOGLE_ADS_REFRESH_TOKEN=your_refresh_token GOOGLE_ADS_LOGIN_CUSTOMER_ID=your_customer_id_without_dashes # SERP API Configuration (optional) SERP_API_KEY=your_serp_api_key

4. Get Google Ads API refresh token

Run the following command to get a refresh token:

npm run get-token

This will open your browser and guide you through the OAuth2 authentication process. The refresh token will be automatically saved to your .env file.

5. Start the server

For development:

npm run dev

For production:

npm start

The server will start on the port specified in your .env file (default: 3000).

API Documentation

API documentation is available at /api-docs when the server is running:

http://localhost:3000/api-docs

MCP Integration

This project includes MCP (Model Context Protocol) integration, allowing AI assistants to use the API. The MCP configuration is in the mcp.json file.

To use this with Smithery:

  1. Go to Smithery
  2. Create a new MCP server
  3. Select the app-seo-ai repository
  4. Configure the server settings
  5. Deploy the server

Available MCP Tools

  • research_keywords - Research keywords related to a given topic or seed keyword
  • analyze_serp - Analyze a SERP (Search Engine Results Page) for a given query
  • analyze_competitors - Analyze competitors for a given keyword or domain
  • _health - Health check endpoint

Example Usage

Research Keywords

// Example request to research keywords fetch('http://localhost:3000/api/keywords/ideas?keyword=seo%20tools&language=en') .then(response => response.json()) .then(data => console.log(data));

Analyze SERP

// Example request to analyze SERP fetch('http://localhost:3000/api/serp/analyze?query=best%20seo%20tools&location=United%20States') .then(response => response.json()) .then(data => console.log(data));

Analyze Competitors

// Example request to analyze competitors fetch('http://localhost:3000/api/competitors/analyze?domain=example.com') .then(response => response.json()) .then(data => console.log(data));

License

MIT

This server cannot be installed

-
security - not tested
F
license - not found
-
quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Provides SEO automation with tools for keyword research, SERP analysis, and competitor analysis through Google Ads API integration, enabling AI assistants to access these capabilities via MCP.

  1. Features
    1. Prerequisites
      1. Setup
        1. 1. Clone the repository
        2. 2. Install dependencies
        3. 3. Configure environment variables
        4. 4. Get Google Ads API refresh token
        5. 5. Start the server
      2. API Documentation
        1. MCP Integration
          1. Available MCP Tools
            1. Example Usage
              1. Research Keywords
              2. Analyze SERP
              3. Analyze Competitors
            2. License

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