-
securityA
license-
qualityA Model Context Protocol (MCP) server that provides AI-powered customer support using Cursor AI and Glama.ai integration.
Last updated -
3
MIT License
Manages environment variables for API keys, database connections, and server configuration settings.
Version control system used for server codebase management and contribution workflow.
Stores user interactions, context metadata, and tracking data for the AI customer support system.
Runtime environment for the MCP server with support for batch processing, priority queuing, and rate limiting.
AI Customer Support Bot - MCP Server
A Model Context Protocol (MCP) server that provides AI-powered customer support using Cursor AI and Glama.ai integration.
Features
Real-time context fetching from Glama.ai
AI-powered response generation with Cursor AI
Batch processing support
Priority queuing
Rate limiting
User interaction tracking
Health monitoring
MCP protocol compliance
Prerequisites
Python 3.8+
PostgreSQL database
Glama.ai API key
Cursor AI API key
Installation
Clone the repository:
git clone <repository-url>
cd <repository-name>
Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
Install dependencies:
pip install -r requirements.txt
Create a
.envfile based on.env.example:
cp .env.example .env
Configure your
.envfile with your credentials:
# API Keys
GLAMA_API_KEY=your_glama_api_key_here
CURSOR_API_KEY=your_cursor_api_key_here
# Database
DATABASE_URL=postgresql://user:password@localhost/customer_support_bot
# API URLs
GLAMA_API_URL=https://api.glama.ai/v1
# Security
SECRET_KEY=your_secret_key_here
# MCP Server Configuration
SERVER_NAME="AI Customer Support Bot"
SERVER_VERSION="1.0.0"
API_PREFIX="/mcp"
MAX_CONTEXT_RESULTS=5
# Rate Limiting
RATE_LIMIT_REQUESTS=100
RATE_LIMIT_PERIOD=60
# Logging
LOG_LEVEL=INFO
Set up the database:
# Create the database
createdb customer_support_bot
# Run migrations (if using Alembic)
alembic upgrade head
Running the Server
Start the server:
python app.py
The server will be available at http://localhost:8000
API Endpoints
1. Root Endpoint
GET /
Returns basic server information.
2. MCP Version
GET /mcp/version
Returns supported MCP protocol versions.
3. Capabilities
GET /mcp/capabilities
Returns server capabilities and supported features.
4. Process Request
POST /mcp/process
Process a single query with context.
Example request:
curl -X POST http://localhost:8000/mcp/process \
-H "Content-Type: application/json" \
-H "X-MCP-Auth: your-auth-token" \
-H "X-MCP-Version: 1.0" \
-d '{
"query": "How do I reset my password?",
"priority": "high",
"mcp_version": "1.0"
}'
5. Batch Processing
POST /mcp/batch
Process multiple queries in a single request.
Example request:
curl -X POST http://localhost:8000/mcp/batch \
-H "Content-Type: application/json" \
-H "X-MCP-Auth: your-auth-token" \
-H "X-MCP-Version: 1.0" \
-d '{
"queries": [
"How do I reset my password?",
"What are your business hours?",
"How do I contact support?"
],
"mcp_version": "1.0"
}'
6. Health Check
GET /mcp/health
Check server health and service status.
Rate Limiting
The server implements rate limiting with the following defaults:
100 requests per 60 seconds
Rate limit information is included in the health check endpoint
Rate limit exceeded responses include reset time
Error Handling
The server returns structured error responses in the following format:
{
"code": "ERROR_CODE",
"message": "Error description",
"details": {
"timestamp": "2024-02-14T12:00:00Z",
"additional_info": "value"
}
}
Common error codes:
RATE_LIMIT_EXCEEDED: Rate limit exceededUNSUPPORTED_MCP_VERSION: Unsupported MCP versionPROCESSING_ERROR: Error processing requestCONTEXT_FETCH_ERROR: Error fetching context from Glama.aiBATCH_PROCESSING_ERROR: Error processing batch request
Development
Project Structure
.
├── app.py # Main application file
├── database.py # Database configuration
├── middleware.py # Middleware (rate limiting, validation)
├── models.py # Database models
├── mcp_config.py # MCP-specific configuration
├── requirements.txt # Python dependencies
└── .env # Environment variables
Adding New Features
Update
mcp_config.pywith new configuration optionsAdd new models in
models.pyif neededCreate new endpoints in
app.pyUpdate capabilities endpoint to reflect new features
Security
All MCP endpoints require authentication via
X-MCP-AuthheaderRate limiting is implemented to prevent abuse
Database credentials should be kept secure
API keys should never be committed to version control
Monitoring
The server provides health check endpoints for monitoring:
Service status
Rate limit usage
Connected services
Processing times
Contributing
Fork the repository
Create a feature branch
Commit your changes
Push to the branch
Create a Pull Request
Flowchart
Verification Badge
License
This project is licensed under the MIT License - see the LICENSE file for details.
Support
For support, please create an issue in the repository or contact the development team.
This server cannot be installed
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.
A Model Context Protocol (MCP) server that provides AI-powered customer support using Cursor AI and Glama.ai integration.
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