Add comprehensive deployment options documentation

Author: infinitimeless

DEPLOYMENT.md

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+# Comprehensive Deployment Options
+
+LMStudio-MCP supports multiple deployment methods to suit different environments and preferences. This document outlines all available deployment options.
+
+## Quick Reference
+
+| Method | Best For | Complexity | Requirements |
+|--------|----------|------------|--------------|
+| **Direct Python** | Development, Testing | Low | Python 3.7+ |
+| **UVX (Recommended)** | Most Users | Low | Python/Node.js |
+| **Pip Install** | Python Developers | Low | Python 3.7+ |
+| **Docker** | Containers, Production | Medium | Docker |
+| **Docker Compose** | Local Development | Medium | Docker + Compose |
+| **Kubernetes** | Enterprise, Scale | High | K8s Cluster |
+
+## Method 1: UVX (Recommended)
+
+UVX is the simplest way to get started:
+
+```bash
+# Install and run directly from GitHub
+uvx https://github.com/infinitimeless/LMStudio-MCP
+
+# Claude MCP Configuration
+{
+  "lmstudio-mcp": {
+    "command": "uvx",
+    "args": ["https://github.com/infinitimeless/LMStudio-MCP"]
+  }
+}
+```
+
+## Method 2: Direct Python Installation
+
+For development or when you want to modify the code:
+
+```bash
+# Clone and setup
+git clone https://github.com/infinitimeless/LMStudio-MCP.git
+cd LMStudio-MCP
+pip install -r requirements.txt
+
+# Run
+python lmstudio_bridge.py
+
+# Claude MCP Configuration
+{
+  "lmstudio-mcp": {
+    "command": "/bin/bash",
+    "args": ["-c", "cd /path/to/LMStudio-MCP && python lmstudio_bridge.py"]
+  }
+}
+```
+
+## Method 3: Pip Installation
+
+Install as a Python package:
+
+```bash
+# Install from GitHub
+pip install git+https://github.com/infinitimeless/LMStudio-MCP.git
+
+# Or install locally
+pip install .
+
+# Run
+lmstudio-mcp
+
+# Claude MCP Configuration
+{
+  "lmstudio-mcp": {
+    "command": "lmstudio-mcp",
+    "args": []
+  }
+}
+```
+
+## Method 4: Docker
+
+See [DOCKER.md](DOCKER.md) for comprehensive Docker deployment guide.
+
+### Quick Docker Start
+
+```bash
+# Build and run
+docker build -t lmstudio-mcp .
+docker run -it --network host lmstudio-mcp
+
+# Or use pre-built image
+docker run -it --network host ghcr.io/infinitimeless/lmstudio-mcp:latest
+
+# Claude MCP Configuration
+{
+  "lmstudio-mcp-docker": {
+    "command": "docker",
+    "args": ["run", "-i", "--rm", "--network=host", "lmstudio-mcp"]
+  }
+}
+```
+
+## Method 5: Docker Compose
+
+```bash
+# Start with compose
+docker-compose up -d
+
+# View logs
+docker-compose logs -f lmstudio-mcp
+
+# Claude MCP Configuration
+{
+  "lmstudio-mcp-compose": {
+    "command": "docker-compose",
+    "args": ["run", "--rm", "lmstudio-mcp"]
+  }
+}
+```
+
+## Method 6: Kubernetes
+
+For enterprise or scaled deployments:
+
+```bash
+# Apply manifests
+kubectl apply -f k8s/
+
+# Check status
+kubectl get pods -l app=lmstudio-mcp
+```
+
+## Method 7: Automated Installation Script
+
+Use the provided installation script:
+
+```bash
+# Download and run installer
+curl -fsSL https://raw.githubusercontent.com/infinitimeless/LMStudio-MCP/main/install.sh | bash
+
+# Or download first
+wget https://raw.githubusercontent.com/infinitimeless/LMStudio-MCP/main/install.sh
+chmod +x install.sh
+./install.sh
+```
+
+The installer will:
+- Detect your environment
+- Install dependencies
+- Set up the bridge
+- Generate MCP configuration
+- Provide next steps
+
+## Environment Variables
+
+All deployment methods support these environment variables:
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `LMSTUDIO_API_BASE` | `http://localhost:1234/v1` | LM Studio API endpoint |
+| `LOG_LEVEL` | `INFO` | Logging level (DEBUG, INFO, WARNING, ERROR) |
+| `TIMEOUT` | `30` | Request timeout in seconds |
+
+Example:
+```bash
+LMSTUDIO_API_BASE=http://127.0.0.1:1234/v1 python lmstudio_bridge.py
+```
+
+## Troubleshooting
+
+### Common Issues
+
+1. **Connection refused**: Ensure LM Studio is running with a model loaded
+2. **404 errors**: Try using `127.0.0.1` instead of `localhost`
+3. **Permission denied**: Check file permissions and Docker access
+4. **Module not found**: Ensure all dependencies are installed
+
+### Platform-Specific Notes
+
+#### macOS
+- Use `localhost` or `127.0.0.1` for LM Studio URL
+- Docker Desktop may require host networking configuration
+
+#### Windows
+- Use Docker Desktop with WSL2 backend
+- Path separators in configuration should use forward slashes
+
+#### Linux
+- Docker may require `sudo` or adding user to docker group
+- Ensure LM Studio is accessible on the network interface
+
+## Performance Optimization
+
+### Resource Requirements
+
+| Deployment | RAM | CPU | Disk |
+|------------|-----|-----|------|
+| Python Direct | ~50MB | Low | Minimal |
+| Docker | ~100MB | Low | ~200MB |
+| Kubernetes | ~150MB | Low | ~300MB |
+
+### Optimization Tips
+
+1. **Use lightweight base images** (already implemented in Dockerfile)
+2. **Enable Docker BuildKit** for faster builds
+3. **Use multi-stage builds** for smaller images
+4. **Configure resource limits** in production
+5. **Use persistent volumes** for logs in container environments
+
+## Security Considerations
+
+### Network Security
+- Bridge requires access to LM Studio on localhost:1234
+- Consider firewall rules for container deployments
+- Use network policies in Kubernetes
+
+### Container Security
+- Runs as non-root user by default
+- Minimal attack surface with slim base image
+- No sensitive data stored in container
+
+### Authentication
+- No authentication required between bridge and LM Studio
+- Claude MCP connection is handled by Claude's MCP framework
+
+## Next Steps
+
+1. Choose your preferred deployment method
+2. Ensure LM Studio is running with a model loaded
+3. Configure Claude MCP settings
+4. Test the connection with a simple prompt
+5. Explore advanced features and customization
+
+For detailed troubleshooting, see [TROUBLESHOOTING.md](TROUBLESHOOTING.md).
+For Docker-specific guidance, see [DOCKER.md](DOCKER.md).
+For contributing, see [CONTRIBUTING.md](CONTRIBUTING.md).