REFACTORING_SUMMARY.md•8.43 kB
# Transport-Agnostic Refactoring Summary
## What Changed
We refactored the CloudNativePG MCP server to support multiple transport modes while keeping stdio as the default for simplicity.
### Key Changes
#### 1. **Separated Transport Layer from Business Logic**
**Before:**
```python
async def main():
from mcp.server.stdio import stdio_server
async with stdio_server() as (read_stream, write_stream):
await mcp.run(read_stream, write_stream, ...)
```
**After:**
```python
# Transport-specific functions
async def run_stdio_transport():
"""stdio transport implementation"""
async def run_http_transport():
"""HTTP/SSE transport (future)"""
async def main():
"""Routes to appropriate transport"""
if args.transport == "stdio":
await run_stdio_transport()
elif args.transport == "http":
await run_http_transport()
```
#### 2. **Added Command-Line Interface**
```bash
# New capabilities
python cnpg_mcp_server.py --help
python cnpg_mcp_server.py --transport stdio
python cnpg_mcp_server.py --transport http --port 3000
```
#### 3. **Improved Initialization**
- Kubernetes clients initialized in dedicated function
- Better error messages during initialization
- Logging to stderr for debugging
#### 4. **Added HTTP Transport Skeleton**
- Placeholder function with clear TODOs
- Implementation notes and examples
- Dependencies pre-listed (commented out)
#### 5. **Updated Documentation**
- Transport modes explained in README
- Architecture section clarifies separation
- New HTTP_TRANSPORT_GUIDE.md for future implementation
## Why These Changes Matter
### ✅ **Keep It Simple Now**
- Default behavior unchanged (stdio)
- No extra dependencies required
- Easy to test locally
- Works great with Claude Desktop
### ✅ **Easy to Extend Later**
- All tool code is transport-agnostic
- HTTP transport requires only one new function
- No refactoring of business logic needed
- Clear path forward documented
### ✅ **Production Ready Path**
- Can scale horizontally with HTTP
- Support multiple concurrent clients
- Deploy as shared team service
- Remote access capability
### ✅ **Best of Both Worlds**
```
Development → Production
stdio → HTTP
Simple → Scalable
Local → Remote
Single → Multi-client
Immediate → When needed
```
## File Changes
### Modified Files
1. **cnpg_mcp_server.py**
- Added `parse_args()` function
- Split `main()` into transport-specific functions
- Added `run_stdio_transport()` and `run_http_transport()`
- Improved initialization and error handling
2. **requirements.txt**
- Added HTTP dependencies (commented out)
- Clear section for future use
3. **README.md**
- New "Transport Modes" section
- Updated "Running the Server" with CLI options
- Enhanced "Architecture" section
### New Files
4. **HTTP_TRANSPORT_GUIDE.md**
- Complete implementation guide
- Security checklist
- Deployment examples
- Troubleshooting tips
## Usage Examples
### Current Usage (stdio - unchanged)
```bash
# Simple - just works
python cnpg_mcp_server.py
# With Claude Desktop
{
"mcpServers": {
"cloudnative-pg": {
"command": "python",
"args": ["/path/to/cnpg_mcp_server.py"]
}
}
}
```
### Future Usage (HTTP - when needed)
```bash
# Install HTTP dependencies
pip install 'mcp[sse]' starlette uvicorn
# Implement run_http_transport() (see guide)
# Run HTTP server
python cnpg_mcp_server.py --transport http --port 3000
# Connect remotely
{
"mcpServers": {
"cloudnative-pg": {
"url": "https://mcp.example.com:3000",
"headers": {"Authorization": "Bearer token"}
}
}
}
```
## Testing Strategy
### Phase 1: Current (stdio)
1. Test basic connectivity ✓
2. Verify tool implementations ✓
3. Use with Claude Desktop ✓
4. Iterate on tools ✓
### Phase 2: When HTTP Needed
1. Uncomment HTTP dependencies
2. Implement `run_http_transport()`
3. Test locally on different port
4. Add authentication
5. Deploy to staging
6. Migrate clients gradually
## Architecture Diagram
```
┌─────────────────────────────────────────────────────┐
│ MCP Tools │
│ @mcp.tool() decorated functions │
│ - list_postgres_clusters() │
│ - get_cluster_status() │
│ - create_postgres_cluster() │
│ - scale_postgres_cluster() │
│ - [future tools...] │
│ │
│ ↓ All tools work with any transport │
└─────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────┐
│ Transport Layer │
│ ┌─────────────────────┐ ┌────────────────────┐ │
│ │ stdio │ │ HTTP/SSE │ │
│ │ ───── │ │ ──────── │ │
│ │ • stdin/stdout │ │ • REST API │ │
│ │ • Local process │ │ • Event stream │ │
│ │ • Simple │ │ • Multi-client │ │
│ │ • Current ✓ │ │ • Future ⏰ │ │
│ └─────────────────────┘ └────────────────────┘ │
└─────────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────────┐
│ Kubernetes API │
│ CloudNativePG operator resources │
└─────────────────────────────────────────────────────┘
```
## Benefits Summary
| Aspect | Before | After |
|--------|--------|-------|
| **Transport** | stdio only | Extensible to HTTP |
| **CLI Args** | None | --transport, --port, --host |
| **Documentation** | Basic | Comprehensive + guides |
| **Testing** | stdio only | Can test both modes |
| **Production** | Not ready | Clear path to production |
| **Complexity** | Same | Same (no added overhead) |
| **Flexibility** | Limited | High |
## Migration Cost
**To add HTTP transport later:**
- Install 3 packages: `mcp[sse]`, `starlette`, `uvicorn`
- Implement 1 function: `run_http_transport()` (~50 lines)
- Add authentication middleware (~30 lines)
- No changes to existing tool code
- Estimated time: 2-4 hours
## Decision Points
### Use stdio when:
- ✓ Personal development
- ✓ Claude Desktop integration
- ✓ Single user
- ✓ Local testing
- ✓ Getting started
### Switch to HTTP when:
- ✓ Multiple team members need access
- ✓ Remote access required
- ✓ Production deployment
- ✓ Shared service model
- ✓ Kubernetes-native deployment
## What Stays the Same
- All tool implementations unchanged
- All business logic unchanged
- Default behavior unchanged (stdio)
- No new dependencies required now
- Testing approach unchanged
- Claude Desktop setup unchanged
## What's Better
- Clear separation of concerns
- Easy to extend without refactoring
- Better documentation
- Production-ready architecture
- Multiple deployment options
- Future-proofed design
## Conclusion
We've kept the server **simple for now** (stdio works great!) while making it **easy to scale later** (HTTP when needed). The refactoring adds **zero complexity** to current usage but provides a **clear path** to production deployment.
**Start simple. Scale when ready. No regrets.** 🚀