mcpField
A
Amazon Ads Manager MCP Server

Amazon Ads Manager MCP Server

Remote
github.com/amekalaCloud & Infra7Updated 84w ago
Repository

About Amazon Ads Manager MCP Server

Amazon Ads Manager MCP Server connects LLMs to Amazon Advertising data through Claude Desktop. It combines campaign and ad group analysis with SQL queries and budget recommendations.

Key features

  1. 01Analyze campaign performance
  2. 02Inspect ad group metrics
  3. 03Get budget optimization recommendations
  4. 04Run custom SQL queries
  5. 05View database schema and metrics

Use cases

  1. 01Review campaign results over a chosen period
  2. 02Check key metrics for an ad group
  3. 03Plan budgets across campaigns
  4. 04Explore advertising data with SQL

MCP support

The server exposes Amazon Advertising database resources and analysis tools to MCP clients. Access uses API key authentication.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://mcp-server-sync-abhilashreddi.replit.app/mcp/sse
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Amazon Ads Manager MCP Server

A Model Context Protocol (MCP) server for managing and analyzing Amazon Advertising data. This server provides a standardized interface for LLMs to interact with your advertising data through the Claude Desktop App.

Features

  • Database Integration: Pre-configured connection to a secure PostgreSQL database
  • API Key Authentication: Secure access through API key validation
  • Real-time Analytics: Access to campaign metrics and performance data
  • Natural Language Interface: Query your advertising data using natural language

Installation

npm install ads-manager-mcp

Quick Start

  1. Install the Claude Desktop App
  2. Create a configuration file claude-desktop-config.json:
{
  "name": "Amazon Ads Manager",
  "version": "1.0.4",
  "description": "Connect to your Amazon Advertising data and analyze campaign performance",
  "mcpServers": {
    "ads-manager": {
      "name": "Ads Manager MCP Server",
      "version": "1.0.4",
      "description": "MCP Server for Amazon Advertising data analysis",
      "transport": "sse",
      "endpoint": "https://mcp-server-sync-abhilashreddi.replit.app/mcp/sse",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY_HERE"
      }
    }
  }
}
  1. Replace YOUR_API_KEY_HERE with your API key
  2. Start using the Claude Desktop App to analyze your advertising data

Available Resources

  • Schema: View database structure and table definitions
  • Metrics: Access advertising performance metrics
  • Campaigns: View campaign configurations and settings
  • Ad Groups: Access ad group details and settings

Available Tools

  • analyzeCampaignPerformance: Analyze campaign metrics and performance
  • analyzeAdGroupPerformance: Get detailed ad group performance analysis
  • optimizeBudget: Get budget optimization recommendations
  • query: Run custom SQL queries against the database

Example Queries

"Show me the structure of all tables in the database"
"Analyze the performance of campaign ABC123 for the last 30 days"
"What are the key metrics for ad group XYZ789?"
"Give me budget recommendations for all campaigns in profile P123"

API Authentication

The server uses API key authentication. Each request must include an Authorization header:

Authorization: Bearer YOUR_API_KEY

Database Connection

The server maintains a connection to a PostgreSQL database. No additional configuration is required as the connection details are pre-configured in the package.

Development

To run the server locally:

# Install dependencies
npm install

# Start the development server
npm run dev

# Build the package
npm run build

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For support, please open an issue in the GitHub repository or contact the maintainers.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.