Kayzen Analytics▌

by springwq
Kayzen Analytics integrates marketing analytics with powerful tools for campaign analysis, reporting, and performance op
Integrates with Kayzen Analytics API to access and analyze marketing campaign data, providing tools for report listing, data fetching with date filtering, and performance optimization insights.
best for
- / Digital marketers analyzing ad campaign performance
- / Data analysts working with advertising metrics
- / Marketing teams optimizing campaign strategies
capabilities
- / List available Kayzen analytics reports
- / Fetch report results with date filtering
- / Analyze campaign performance data
- / Access advertising metrics and insights
- / Manage authentication tokens automatically
what it does
Connects to Kayzen Analytics API to retrieve and analyze advertising campaign data and performance metrics.
about
Kayzen Analytics is a community-built MCP server published by springwq that provides AI assistants with tools and capabilities via the Model Context Protocol. Kayzen Analytics integrates marketing analytics with powerful tools for campaign analysis, reporting, and performance op It is categorized under analytics data.
how to install
You can install Kayzen Analytics in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Kayzen Analytics is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
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 identifiername: Report nametype: 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 fetchstart_date(string, optional): Start date in YYYY-MM-DD formatend_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: ^1.7.0axios: ^1.8.3dotenv: ^16.4.7zod: ^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
FAQ
- What is the Kayzen Analytics MCP server?
- Kayzen Analytics is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Kayzen Analytics?
- This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Ratings
4.5★★★★★10 reviews- ★★★★★Shikha Mishra· Oct 10, 2024
Kayzen Analytics is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Piyush G· Sep 9, 2024
We evaluated Kayzen Analytics against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: Kayzen Analytics is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Sakshi Patil· Jul 7, 2024
Kayzen Analytics reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ganesh Mohane· Jun 6, 2024
I recommend Kayzen Analytics for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: Kayzen Analytics surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Dhruvi Jain· Apr 4, 2024
Kayzen Analytics has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Rahul Santra· Mar 3, 2024
According to our notes, Kayzen Analytics benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Pratham Ware· Feb 2, 2024
We wired Kayzen Analytics into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Yash Thakker· Jan 1, 2024
Kayzen Analytics is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.