nexlayer-mcp-backup

sasdeployer/nexlayer-mcp-backup

3.1

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The Nexlayer MCP Server is a Model Context Protocol server designed to facilitate the deployment and management of applications on the Nexlayer cloud platform using AI agents.

Tools
15
Resources
0
Prompts
0

Nexlayer MCP Server

A Model Context Protocol (MCP) server that provides tools for deploying and managing applications on the Nexlayer cloud platform through AI agents.

Features

This MCP server provides 14 essential tools for complete application deployment workflows with AI agent optimization:

Core Deployment Tools

  • nexlayer_complete_deployment - NEW Complete 6-step workflow orchestrator (recommended for new deployments)
  • nexlayer_deploy - Final deployment step (requires prepared YAML with ttl.sh images)
  • nexlayer_extend_deployment - Extend deployment duration using session token
  • nexlayer_claim_deployment - Claim ownership of a deployment
  • nexlayer_get_schema - Get current YAML schema with LLM-friendly examples and validation
  • nexlayer_add_deployment_reservation - Reserve application names to prevent conflicts
  • nexlayer_remove_deployment_reservation - Release reserved application names
  • nexlayer_get_reservations - List all active deployment reservations
  • nexlayer_feedback - Send feedback to Nexlayer team

Repository Analysis Tools

  • nexlayer_clone_repo - Clone GitHub repositories for analysis
  • nexlayer_analyze_repository - Deep project analysis with framework detection
  • nexlayer_detect_env_and_secrets - Scan for environment variables and secrets

Container Building Tools

  • nexlayer_build_images - Build container images using Dagger and push to ttl.sh

File Generation Tools

  • nexlayer_generate_intelligent_dockerfile - AI-powered Dockerfile generation (overwrites existing broken Dockerfiles)
  • nexlayer_generate_intelligent_yaml - Schema-driven YAML configuration generation

Advanced Features

  • 6-Step Workflow Orchestration: Guided deployment process with nexlayer_complete_deployment
  • Schema-Driven YAML Generation: Automatically fetches and uses current Nexlayer schema
  • Dockerfile Overwrite Protection: Automatically fixes broken existing Dockerfiles
  • AI Agent Optimization: Automatically detects and optimizes for different AI clients (Claude, Cursor, Windsurf)
  • Session Tracking: Complete deployment lifecycle tracking with performance metrics
  • Structured Logging: Comprehensive logging with parameter sanitization
  • Error Handling: Detailed error messages with troubleshooting guidance
  • Security: Built-in parameter validation and sanitization

Installation

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "nexlayer": {
      "command": "npx",
      "args": ["nexlayer-mcp@latest"]
    }
  }
}

Configuration file locations:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Cursor IDE

Add to your cursor-mcp-config.json:

{
  "mcpServers": {
    "nexlayer": {
      "command": "npx",
      "args": ["nexlayer-mcp@latest"]
    }
  }
}

Other AI Clients

Configure in your MCP settings using the same command structure.

API Integration

The server integrates with these Nexlayer API endpoints:

Core Deployment

  • POST /startUserDeployment - Deploy applications with validation
  • POST /extendDeployment - Extend deployment duration
  • POST /claimDeployment - Claim deployment ownership

Validation & Schema

  • GET /schema - Get YAML schema for configuration
  • POST /validate - Validate YAML configuration
  • POST /feedback - Submit feedback to Nexlayer team

Reservation Management

  • POST /addDeploymentReservation - Reserve application names
  • POST /removeDeploymentReservation - Release name reservations
  • GET /getReservations - List active reservations

Advanced Features

  • Agent metadata injection for analytics
  • Session token management
  • Error categorization and guidance

Authentication

Authentication uses session tokens:

  • Initial deployments return session tokens
  • Management operations require session tokens
  • Tokens are automatically managed by the tools
  • Agent metadata is included in all API calls

Usage

Basic Deployment

"Deploy https://github.com/username/repository to Nexlayer"

Advanced Deployment

"Deploy with custom YAML configuration"
"Auto-generate deployment config from project analysis"
"Validate my YAML before deploying"

Deployment Management

"Extend my deployment with session token abc123"
"Claim deployment my-app with token def456"
"Send feedback about my deployment experience"

6-Step Deployment Workflow

  1. Clone - Download repository from GitHub with nexlayer_clone_repo
  2. Analyze - Detect frameworks, dependencies, and configuration with nexlayer_analyze_repository
  3. Generate - Create optimized Dockerfiles with nexlayer_generate_intelligent_dockerfile
  4. Build - Build container images with nexlayer_build_images using Dagger
  5. Configure - Generate Nexlayer YAML with nexlayer_generate_intelligent_yaml
  6. Deploy - Deploy to Nexlayer platform with nexlayer_deploy

Development

Project Structure

src/
├── server.ts           # MCP server initialization and agent detection
├── tools/              # Modular tool implementations
│   ├── registry.ts     # Centralized tool registration system
│   ├── core.ts         # Deployment lifecycle tools (5 tools)
│   ├── analysis.ts     # Repository analysis tools (3 tools)
│   ├── dagger.ts       # Container building tools (1 tool)
│   └── generator.ts    # File generation tools (2 tools)
├── services/           # External service integrations
├── utils/              # Logging, tracing, and utilities
├── prompts/            # AI agent guidance prompts
└── agent/              # AI agent detection and optimization

Adding New Tools

  1. Define interfaces in types/nexlayer.ts
  2. Add API methods in services/nexlayer-api.ts
  3. Implement in appropriate tool module
  4. Register in module's registerTools() method
  5. Follow the standardized tool implementation pattern

Building

npm install
npm run build

Error Handling

All tools include comprehensive error handling with:

  • Detailed error messages with context
  • Troubleshooting guidance and solutions
  • Session tracking for debugging
  • Parameter sanitization for security
  • Error categorization (validation, resource, network, etc.)

Performance & Security

  • Rate Limiting: Built-in protection against abuse
  • Input Validation: Comprehensive parameter validation
  • Error Sanitization: Never expose internal system details
  • Resource Management: Automatic cleanup of temporary files
  • Caching: Optimized API response caching

License

MIT

Support