# Local vs Cloud Deployment Strategy
## Problem
The Railway cloud deployment works perfectly for the MCP protocol, but cannot access local file paths. Users need to analyze local Java projects.
## Two Solutions
### Option 1: Cloud MCP with File Content Upload ⚠️ (Complex)
**How it works:**
- Client sends file contents (base64 encoded, or zip archive) to cloud server
- Server processes content in memory
- Returns analysis results
**Pros:**
- ✅ Single deployment (cloud only)
- ✅ No local installation needed
- ✅ Centralized updates
**Cons:**
- ❌ Large projects = large payloads (network overhead)
- ❌ Requires changes to all tool signatures
- ❌ Complex implementation (file upload, temp storage, cleanup)
- ❌ Security concerns (uploading source code)
- ❌ Slower (network latency + upload time)
**Implementation Required:**
```java
@McpTool(name = "analyzeJakartaReadiness")
public String analyzeJakartaReadiness(
@McpToolParam(description = "Project path (for local) OR project files (base64 zip)") String projectPath,
@McpToolParam(description = "Optional: Base64-encoded zip of project files") String projectFiles
) {
if (projectFiles != null) {
// Extract zip, analyze in temp directory
} else {
// Use projectPath (local filesystem)
}
}
```
### Option 2: NPM Package for Local STDIO ⭐ (Recommended)
**How it works:**
- User installs via `npm install -g jakarta-migration-mcp`
- Runs locally via STDIO transport
- Full filesystem access
- No network overhead
**Pros:**
- ✅ **Best performance** (no network latency)
- ✅ **Full filesystem access** (works with local paths)
- ✅ **Simple implementation** (already have package.json + index.js)
- ✅ **Better UX** (works offline, faster)
- ✅ **Privacy** (code never leaves local machine)
- ✅ **Standard MCP pattern** (stdio is designed for local tools)
**Cons:**
- ❌ Requires local installation
- ❌ Need to distribute JAR file (can bundle or download)
**Implementation:**
- ✅ Already have `package.json` and `index.js`
- ✅ Just need to ensure JAR is available (download or bundle)
- ✅ Works with existing stdio transport
## Recommendation: **Option 2 (NPM Package)**
### Why NPM Package is Better
1. **MCP Design Philosophy**: STDIO transport is specifically designed for local tools. Cloud HTTP is for remote services.
2. **Performance**: Local execution is always faster than cloud + file upload.
3. **Privacy**: Source code never leaves the user's machine.
4. **Simplicity**: No need to change tool signatures or handle file uploads.
5. **User Experience**:
- `npm install -g jakarta-migration-mcp`
- Add to Cursor config
- Done!
6. **Hybrid Approach**:
- Cloud deployment for discovery (Glama.ai listing)
- NPM package for actual usage (local execution)
## Implementation Plan
### Phase 1: NPM Package (Do This First)
1. **Update `package.json`**:
- Set correct package name
- Add repository URL
- Add author info
2. **Update `index.js`**:
- Ensure it correctly launches the JAR
- Handle Java detection
- Provide helpful error messages
3. **Update `scripts/postinstall.js`**:
- Download JAR from GitHub releases (or bundle it)
- Verify Java installation
- Set up executable permissions
4. **Test locally**:
```bash
npm link
jakarta-migration-mcp --help
```
5. **Publish to npm**:
```bash
npm publish
```
### Phase 2: Documentation
1. **Update README** with npm installation:
```bash
npm install -g jakarta-migration-mcp
```
2. **Update Cursor config example**:
```json
{
"mcpServers": {
"jakarta-migration": {
"command": "jakarta-migration-mcp"
}
}
}
```
3. **Update Glama.json** to mention both:
- Cloud: For discovery/testing
- NPM: For production use
### Phase 3: Optional - Cloud File Upload (Later)
If needed later, can add optional file upload support:
- Add `projectFiles` parameter (optional)
- Only use if `projectPath` doesn't exist
- Keep backward compatibility
## Current Status
✅ **NPM Infrastructure**: Already exists
- `package.json` ✅
- `index.js` ✅
- `scripts/postinstall.js` ✅
⏭️ **Needs**:
- Verify JAR path/availability
- Test npm installation
- Publish to npm
## User Experience
### With NPM Package
```bash
# Install
npm install -g jakarta-migration-mcp
# Use in Cursor (automatically via MCP config)
```
**Cursor Config:**
```json
{
"mcpServers": {
"jakarta-migration": {
"command": "jakarta-migration-mcp"
}
}
}
```
**Result**:
- ✅ Works with local file paths
- ✅ Fast (no network)
- ✅ Private (code stays local)
- ✅ Simple setup
### With Cloud (Current)
**Cursor Config:**
```json
{
"mcpServers": {
"jakarta-migration-railway": {
"type": "streamable-http",
"url": "https://jakartamigrationmcp-production.up.railway.app/mcp/streamable-http"
}
}
}
```
**Result**:
- ❌ Can't access local files
- ⚠️ Good for discovery/testing
- ✅ Good for remote projects (if we add file upload later)
## Conclusion
**Recommended Approach**:
1. **Ship NPM package** for local usage (primary)
2. **Keep cloud deployment** for discovery/marketing (secondary)
3. **Optional**: Add file upload to cloud later if needed
This gives users the best of both worlds:
- **Easy discovery** via Glama.ai (cloud URL)
- **Best performance** via npm (local execution)
