Which integrations are available for this server?

Provides time filtering tools that can be integrated into Langflow AI workflows, enabling automated dashboard time period management through MCP protocol

How do I use CX TimeFilter MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@CX TimeFilter MCP Server set the Overview tab to the last 7 days" 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.

CX TimeFilter MCP Server

A Model Context Protocol (MCP) server providing time filter tools for CX Dashboard. This server exposes time filtering functionality that can be used by any MCP-compatible client, including Langflow.

🎯 Features

Set Predefined Time Periods: Last Month, Last 7 days, This Quarter, etc.
Set Custom Date Ranges: Specify exact start and end dates
List Available Periods: Get all supported time periods
HTTP-based MCP Protocol: Easy integration with any MCP client
Optional Authentication: API key protection
Comprehensive Validation: Input validation and error handling

🚀 Quick Start

1. Installation

# Clone or create the project directory mkdir cx-timefilter-mcp-server cd cx-timefilter-mcp-server # Install dependencies npm install

2. Configuration

# Copy environment template cp env.example .env # Edit .env file PORT=3000 NODE_ENV=development MCP_API_KEY=your-secret-api-key-here ALLOWED_ORIGINS=http://localhost:3001,https://your-langflow-instance.com

3. Run the Server

# Development mode npm run dev # Production mode npm start # Run tests npm test

4. Verify Installation

# Health check curl http://localhost:3000/health # List available tools curl http://localhost:3000/mcp/tools # Test a tool (with API key if configured) curl -X POST http://localhost:3000/mcp/tools/call \ -H "Content-Type: application/json" \ -H "Authorization: Bearer your-api-key" \ -d '{ "name": "set_time_period", "arguments": { "timePeriodName": "Last Month", "tabName": "Overview" } }'

🛠️ Available Tools

1. set_time_period

Set a predefined time period for dashboard tabs.

Parameters:

timePeriodName (string): Exact name of the time period
tabName (string): Dashboard tab name

Example:

{ "name": "set_time_period", "arguments": { "timePeriodName": "Last Month", "tabName": "Overview" } }

2. set_custom_date_range

Set a custom date range with specific start and end dates.

Parameters:

startDate (string): Start date in YYYY-MM-DD format
endDate (string): End date in YYYY-MM-DD format
tabName (string): Dashboard tab name

Example:

{ "name": "set_custom_date_range", "arguments": { "startDate": "2024-01-01", "endDate": "2024-01-31", "tabName": "Comparison" } }

3. list_time_periods

List all available predefined time periods.

Parameters: None

Example:

{ "name": "list_time_periods", "arguments": {} }

🔗 API Endpoints

Endpoint	Method	Description
`/health`	GET	Health check
`/mcp/info`	GET	MCP protocol information
`/mcp/tools`	GET	List available tools
`/mcp/tools/call`	POST	Execute a tool
`/mcp`	POST	Full MCP protocol endpoint

🔐 Authentication

The server supports optional API key authentication:

Set API Key: Add MCP_API_KEY=your-secret-key to .env
Include in Requests: Add Authorization: Bearer your-secret-key header
Alternative Formats: ApiKey your-secret-key or Key your-secret-key

🌐 Langflow Integration

Step 1: Add MCP Tools Component

Open your Langflow project
Add an "MCP Tools" component
Configure the connection

Step 2: Configure Connection

{ "serverName": "CX TimeFilter Server", "connectionMode": "HTTP", "serverUrl": "http://localhost:3000", "apiKey": "your-api-key", "endpoints": { "tools": "/mcp/tools", "call": "/mcp/tools/call" } }

Step 3: Use Tools in Flows

The tools will appear in Langflow and can be used in your AI workflows.

📦 Deployment

Railway (Recommended)

# Install Railway CLI npm install -g @railway/cli # Login and deploy railway login railway init railway up

Render

Connect your GitHub repository
Set environment variables
Deploy automatically

Docker

FROM node:18-alpine WORKDIR /app COPY package*.json ./ RUN npm install COPY . . EXPOSE 3000 CMD ["npm", "start"]

🧪 Testing

# Run built-in tests npm test # Manual testing with curl curl -X POST http://localhost:3000/mcp/tools/call \ -H "Content-Type: application/json" \ -d '{ "name": "list_time_periods", "arguments": {} }'

📊 Supported Time Periods

Calendar Periods:

All Time, Today, Yesterday
This Week, Last Week
This Month, Last Month
This Quarter, Last Quarter
This Year, Last Year

Rolling Periods:

Last 24 hours, Last 7 days, Last 14 days
Last 30 days, Last 90 days, Last 180 days
Last 12 Months

Custom Periods:

Any date range in YYYY-MM-DD format

🔧 Development

Project Structure

cx-timefilter-mcp-server/ ├── src/ │ ├── server.js # Main server │ ├── tools/ │ │ └── timefilter.js # Time filter tools │ ├── utils/ │ │ └── mcp-protocol.js # MCP utilities │ ├── middleware/ │ │ └── auth.js # Authentication │ └── test.js # Test suite ├── package.json ├── .env └── README.md

Adding New Tools

Create tool definition in src/tools/
Add validation schema
Implement execute function
Export in tools array
Update README

🐛 Troubleshooting

Common Issues:

Port already in use: Change PORT in .env
CORS errors: Update ALLOWED_ORIGINS in .env
Auth failures: Check MCP_API_KEY configuration
Tool not found: Verify tool name matches exactly

Debug Mode:

NODE_ENV=development npm start

📄 License

MIT License - see LICENSE file for details.

🤝 Contributing

Fork the repository
Create a feature branch
Make your changes
Add tests
Submit a pull request

Ready to integrate with Langflow and start filtering time periods via MCP! 🎉

CX TimeFilter MCP Server

CX TimeFilter MCP Server

🎯 Features

🚀 Quick Start

1. Installation

2. Configuration

3. Run the Server

4. Verify Installation

🛠️ Available Tools

1. set_time_period

2. set_custom_date_range

3. list_time_periods

🔗 API Endpoints

🔐 Authentication

🌐 Langflow Integration

Step 1: Add MCP Tools Component

Step 2: Configure Connection

Step 3: Use Tools in Flows

📦 Deployment

Railway (Recommended)

Render

Docker

🧪 Testing

📊 Supported Time Periods

🔧 Development

Project Structure

Adding New Tools

🐛 Troubleshooting

📄 License

🤝 Contributing

Resources

New MCP Servers

Latest Blog Posts

MCP directory API