Kayzen Analytics MCP Server

Kayzen Analytics MCP Server

An implementation that enables AI models to access and analyze Kayzen advertising campaign data through a standardized interface with features like automated authentication and report management.

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Visit Server

README

Kayzen Analytics MCP Server

A Model Context Protocol (MCP) server implementation for interacting with Kayzen Analytics API. This package enables AI models to access and analyze Kayzen advertising campaign data through a standardized interface.

Features

  • Automated Authentication: Built-in token management with automatic refresh mechanism
  • Report Management: Easy access to Kayzen analytics reports
  • Error Handling: Comprehensive error handling for API interactions
  • TypeScript Support: Full TypeScript implementation with type definitions
  • Environment Based Configuration: Simple setup using environment variables

Installation

npm install @feedmob-ai/kayzen-mcp

Configuration

Create a .env file with your Kayzen credentials:

KAYZEN_USERNAME=your_username
KAYZEN_PASSWORD=your_password
KAYZEN_BASIC_AUTH=your_basic_auth_token
KAYZEN_BASE_URL=https://api.kayzen.io/v1  # Optional, defaults to this value

Usage

Basic Setup

import { KayzenMCPServer } from '@feedmob-ai/kayzen-mcp';

const server = new KayzenMCPServer();
server.start();

Available Tools

1. list_reports

Lists all available reports from Kayzen Analytics.

  • Inputs: None
  • Returns: Array of report objects containing:
    • id: Report identifier
    • name: Report name
    • type: Report type
const reports = await server.tools.list_reports();

2. get_report_results

Retrieves results for a specific report.

  • Inputs:
    • report_id (string, required): ID of the report to fetch
    • start_date (string, optional): Start date in YYYY-MM-DD format
    • end_date (string, optional): End date in YYYY-MM-DD format
  • Returns: Report data and metadata
const results = await server.tools.get_report_results({
  report_id: 'report_id',
  start_date: '2024-01-01',  // optional
  end_date: '2024-01-31'     // optional
});

3. analyze_report_results (Prompt)

Analyzes report results and provides insights.

  • Inputs:
    • report_id (string): ID of the report to analyze
  • Analysis includes:
    • Performance metrics
    • Key trends
    • Areas for optimization
    • Unusual patterns or anomalies

Setup

Usage with Claude Desktop

To use this with Claude Desktop, add the following to your claude_desktop_config.json:

NPX

{
  "mcpServers": {
    "github": {
      "command": "npx",
      "args": [
        "-y",
        "@feedmob-ai/kayzen-mcp"
      ],
      "env": {
        "KAYZEN_USERNAME": "username",
        "KAYZEN_PASSWORD": "pasword",
        "KAYZEN_BASIC_AUTH": "auth token"
      }
    }
  }
}

Development

Prerequisites

  • Node.js (v16 or higher)
  • npm (v7 or higher)
  • Kayzen API credentials

Scripts

# Install dependencies
npm install

# Build the project
npm run build

# Start the server
npm start

# Development mode with hot-reload
npm run dev

Project Structure

kayzen-mcp/
├── src/
│   ├── server.ts        # MCP server implementation
│   └── kayzen-client.ts # Kayzen API client
├── dist/               # Compiled JavaScript
└── package.json       # Project configuration

Dependencies

Main dependencies:

  • @modelcontextprotocol/sdk: ^1.7.0
  • axios: ^1.8.3
  • dotenv: ^16.4.7
  • zod: ^3.24.2

Error Handling

The server handles various error scenarios:

  • Authentication failures
  • Invalid API requests
  • Network issues
  • Token expiration and refresh
  • Invalid parameters

License

MIT License

Author

FeedMob

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