Program for Algorithmic Search Engine Optimization (SEO) Enhancement

This utility facilitates automated SEO operations and intelligent content refinement, leveraging seamless connectivity with the Google Ads Keyword Planner suite for market research and competitive intelligence.

Core Functionalities

• Keyword Discovery leveraging the Google Ads remote procedure call interface
• SERP ranking pattern identification and analysis
• Competitive digital landscape assessment
• Generation of optimization mandates and strategic advisories
• Adherence to the Model Context Protocol (MCP) for advanced assistant interfacing

System Requirements

• Runtime Environment: Node.js (version 14 or newer)
• Package Management: npm or yarn
• Credentials: Valid Google Ads entity access authorization
• Cloud Setup: An active Google Cloud Platform instance where the Google Ads API has been successfully provisioned

Deployment Procedure

Phase 1: Source Code Retrieval

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

Phase 2: Dependency Loading

npm install

Phase 3: Environment Variable Seeding

Duplicate the template configuration file:

cp .env.example .env

Modify the .env file to input proprietary Google Ads access keys:

# Runtime Environment Configuration
PORT=3000
NODE_ENV=development

# Google Ads API Authorization Parameters
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

# External SERP Fetching Key (Optional)
SERP_API_KEY=your_serp_api_key

Phase 4: Securing OAuth Refresh Token

Execute the following script to initiate the token acquisition workflow:

npm run get-token

This action triggers a browser redirection for OAuth2 validation; the resulting refresh token is automatically persisted within the .env file.

Phase 5: Application Initiation

For local iterative refinement:

npm run dev

For production deployment:

npm start

The service instance will commence operation on the designated network port as specified in the environment configuration (default port is 3000).

Interface Documentation

The interface specifications are accessible via the /api-docs endpoint once the service is operational:

http://localhost:3000/api-docs

MCP Interoperability Layer

This deployment incorporates MCP (Model Context Protocol) compliance, enabling external intelligent agents to interface with the service endpoints. The configuration governing MCP behavior resides in the mcp.json artifact.

Instructions for Smithery Integration:

1. Navigate to Smithery
2. Establish a novel MCP server instance
3. Designate the app-seo-ai repository as the source
4. Adjust the server operational parameters as required
5. Finalize deployment

Registered MCP Endpoints

• research_keywords - Tool for eliciting search term ideas based on a thematic input or foundational keyword.
• analyze_serp - Utility for deconstructing the result set of a specific search query.
• analyze_competitors - Functionality to assess rival digital presences relative to a target keyword or established domain.
• _health - Standard system operational status probe.

Illustrative Interaction Samples

Keyword Discovery Probe

// Illustrative invocation for retrieving keyword concepts
fetch('http://localhost:3000/api/keywords/ideas?keyword=seo%20tools&language=en')
  .then(response => response.json())
  .then(data => console.log(data));

SERP Examination Request

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

Competitive Entity Scrutiny

// Illustrative invocation for domain comparison
fetch('http://localhost:3000/api/competitors/analyze?domain=example.com')
  .then(response => response.json())
  .then(data => console.log(data));

Legal Disposition

Licensed under the MIT framework