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

This server cannot be installed

security - not tested

license - not found

quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

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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