Used as an HTTP client for making API requests to the Kayzen Analytics API.
Enables environment-based configuration for Kayzen credentials through .env files.
Provides the runtime environment for the MCP server, requiring v16 or higher.
Package manager used for installation and running scripts, requiring v7 or higher.
Provides type safety with full TypeScript implementation and type definitions.
Used for schema validation and type safety in API interactions.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Kayzen Analytics MCP Server show me the performance report for last month's campaigns"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
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
Related MCP server: Marketing Automation MCP Server
npm install @feedmob-ai/kayzen-mcpCreate 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 valueimport { KayzenMCPServer } from '@feedmob-ai/kayzen-mcp';
const server = new KayzenMCPServer();
server.start();list_reportsLists 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();get_report_resultsRetrieves 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
});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
To use this with Claude Desktop, add the following to your claude_desktop_config.json:
{
"mcpServers": {
"github": {
"command": "npx",
"args": [
"-y",
"@feedmob-ai/kayzen-mcp"
],
"env": {
"KAYZEN_USERNAME": "username",
"KAYZEN_PASSWORD": "pasword",
"KAYZEN_BASIC_AUTH": "auth token"
}
}
}
}Node.js (v16 or higher)
npm (v7 or higher)
Kayzen API credentials
# Install dependencies
npm install
# Build the project
npm run build
# Start the server
npm start
# Development mode with hot-reload
npm run devkayzen-mcp/
├── src/
│ ├── server.ts # MCP server implementation
│ └── kayzen-client.ts # Kayzen API client
├── dist/ # Compiled JavaScript
└── package.json # Project configurationMain dependencies:
@modelcontextprotocol/sdk: ^1.7.0
axios: ^1.8.3
dotenv: ^16.4.7
zod: ^3.24.2
The server handles various error scenarios:
Authentication failures
Invalid API requests
Network issues
Token expiration and refresh
Invalid parameters
MIT License
FeedMob
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | No | End date in YYYY-MM-DD format | |
| report_id | Yes | ID of the report to fetch results for | |
| start_date | No | Start date in YYYY-MM-DD format |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0get_report_resultslist_reportsThe two tools have clearly distinct purposes: 'get_report_results' appears to retrieve specific report data, while 'list_reports' enumerates available reports. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on whether it needs to list reports or fetch results from a particular report.
Both tools follow a consistent verb_noun naming pattern ('get_report_results' and 'list_reports'), using snake_case throughout. The verbs 'get' and 'list' are standard and predictable, making the tool names easy to understand and use without confusion.
With only two tools, the server feels under-scoped for an analytics domain, which typically involves operations like creating, updating, filtering, or deleting reports. This minimal set may force agents to work around gaps, such as being unable to generate new reports or modify existing ones, limiting functionality.
The tool surface is severely incomplete for analytics: it allows listing and retrieving reports but lacks essential operations like creating, updating, deleting, or filtering reports. This creates significant gaps that will likely cause agent failures when trying to perform common analytics tasks beyond basic read-only access.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Access Google & Meta Ads data via AI. Analyse campaign performance in seconds.
Conversational access to advertising performance data, creative analysis, and campaign insights
Conversational access to advertising performance data, creative analysis, and campaign insights
Marketing intelligence API for AI agents. Real campaign data, not LLM guesses.
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