- Add get_node_essentials tool for 10-20 essential properties only - Add search_node_properties for targeted property search - Add get_node_for_task with 14 pre-configured templates - Add validate_node_config for comprehensive validation - Add get_property_dependencies for visibility analysis - Implement PropertyFilter service with curated essentials - Implement ExampleGenerator with working examples - Implement TaskTemplates for common workflows - Implement ConfigValidator with security checks - Implement PropertyDependencies for dependency analysis - Enhance property descriptions to 100% coverage - Add version information to essentials response - Update documentation with new tools Response sizes reduced from 100KB+ to <5KB for better AI agent usability. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
299 lines
7.7 KiB
Markdown
299 lines
7.7 KiB
Markdown
# MCP Implementation Technical Decisions
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## Architecture Decisions
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### 1. Incremental Enhancement vs. Complete Rewrite
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**Decision**: Incremental enhancement with backward compatibility
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**Rationale**:
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- Minimizes risk and allows testing at each stage
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- Existing tools continue to work during migration
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- Can deliver value immediately without waiting for full implementation
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- Easier rollback if issues arise
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**Implementation**:
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- New tools alongside existing ones (get_node_essentials + get_node_info)
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- Feature flags for gradual rollout
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- Shared service layer for data access
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### 2. Data Storage Strategy
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**Decision**: Hybrid approach - start with JSON parsing, migrate to relational structure
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**Phase 1** (Immediate):
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- Parse existing JSON property schemas on-demand
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- Cache parsed results in memory
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- Store essential property lists in configuration files
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**Phase 2** (Month 2):
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- Migrate to property-level relational tables
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- Maintain JSON schemas for backward compatibility
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- Use materialized views for performance
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**Rationale**:
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- Delivers immediate improvements without database changes
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- Allows time to design optimal schema
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- Provides fallback during migration
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### 3. Property Categorization
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**Decision**: Multi-dimensional categorization
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**Categories**:
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1. **By Importance**: required > essential > common > advanced
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2. **By Function**: authentication, request, response, processing, output
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3. **By Complexity**: basic, intermediate, expert
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4. **By Usage**: always, frequent, occasional, rare
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**Implementation**:
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```typescript
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interface PropertyMetadata {
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importance: 'required' | 'essential' | 'common' | 'advanced';
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category: 'auth' | 'request' | 'response' | 'processing' | 'output';
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complexity: 'basic' | 'intermediate' | 'expert';
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usageFrequency: number; // 0-100
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}
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```
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### 4. Property Deduplication Strategy
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**Decision**: Single source of truth with condition variants
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**Approach**:
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- Each property appears once in the data model
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- Conditions stored as metadata
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- Runtime resolution based on current configuration
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**Example**:
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```typescript
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{
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name: "httpMethod",
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type: "dynamic",
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baseType: "select",
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variants: [
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{
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condition: { multipleMethods: false },
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config: { multiple: false, default: "GET" }
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},
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{
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condition: { multipleMethods: true },
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config: { multiple: true, default: ["GET", "POST"] }
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}
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]
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}
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```
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### 5. API Response Optimization
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**Decision**: Progressive disclosure with explicit detail levels
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**Levels**:
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1. **Minimal**: Just enough to identify and use (1-2KB)
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2. **Essential**: Common use cases covered (5KB)
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3. **Standard**: Full functional details (20KB)
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4. **Complete**: Everything including metadata (100KB+)
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**Implementation**:
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```typescript
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interface NodeInfoRequest {
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nodeType: string;
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level: 'minimal' | 'essential' | 'standard' | 'complete';
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include?: ('examples' | 'documentation' | 'source')[];
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propertyFilter?: {
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categories?: string[];
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importance?: string[];
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};
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}
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```
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### 6. Caching Strategy
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**Decision**: Multi-layer caching with TTL
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**Layers**:
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1. **Request Cache**: 5-minute TTL for identical requests
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2. **Parsed Property Cache**: 1-hour TTL for parsed structures
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3. **Essential Properties**: Pre-computed at startup
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4. **Database Query Cache**: 30-minute TTL for complex queries
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**Implementation**:
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```typescript
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class CacheManager {
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private requestCache = new LRUCache<string, any>({ ttl: 5 * 60 * 1000 });
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private propertyCache = new LRUCache<string, ParsedProperty[]>({ ttl: 60 * 60 * 1000 });
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private essentialsCache = new Map<string, NodeEssentials>();
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}
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```
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### 7. Error Handling Philosophy
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**Decision**: Graceful degradation with helpful fallbacks
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**Principles**:
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- Never return empty responses if data exists
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- Provide partial data rather than errors
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- Include suggestions for fixing issues
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- Log errors but don't expose internals
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**Example**:
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```typescript
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try {
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return getOptimizedResponse(nodeType);
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} catch (error) {
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logger.warn(`Failed to optimize response for ${nodeType}, falling back`);
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return {
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...getBasicResponse(nodeType),
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_warning: "Using simplified response due to processing error"
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};
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}
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```
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### 8. Search Implementation
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**Decision**: Multi-strategy search with ranking
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**Strategies**:
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1. **Exact match**: Property name exact match (weight: 10)
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2. **Prefix match**: Property name starts with query (weight: 8)
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3. **Contains match**: Property name contains query (weight: 5)
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4. **Description match**: Description contains query (weight: 3)
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5. **Fuzzy match**: Levenshtein distance < 2 (weight: 1)
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**Ranking factors**:
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- Match quality
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- Property importance
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- Usage frequency
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- Position in hierarchy
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### 9. Task Template Design
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**Decision**: Declarative templates with validation
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**Structure**:
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```typescript
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interface TaskTemplate {
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id: string;
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name: string;
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description: string;
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category: string;
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difficulty: 'beginner' | 'intermediate' | 'advanced';
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// What this task accomplishes
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objectives: string[];
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// Required configuration
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nodeType: string;
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configuration: object;
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// User inputs needed
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inputs: Array<{
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property: string;
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description: string;
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example?: any;
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validation?: string; // Regex or function name
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}>;
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// Additional options
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enhancements: Array<{
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property: string;
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description: string;
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when?: string; // Condition for relevance
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}>;
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// Success criteria
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validation: {
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required: string[];
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warnings: Array<{
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condition: string;
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message: string;
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}>;
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};
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}
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```
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### 10. Performance Targets
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**Decision**: Strict performance budgets
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**Targets**:
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- get_node_essentials: <50ms response time
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- search_node_properties: <100ms for 1000 properties
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- validate_node_config: <20ms
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- Memory overhead: <100MB for full cache
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- Startup time: <5s including cache warming
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**Monitoring**:
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```typescript
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class PerformanceMonitor {
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private metrics = new Map<string, number[]>();
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track(operation: string, duration: number) {
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if (duration > PERFORMANCE_BUDGETS[operation]) {
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logger.warn(`Performance budget exceeded: ${operation} took ${duration}ms`);
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}
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}
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}
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```
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## Security Considerations
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### 1. Input Validation
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- Sanitize all user inputs
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- Validate node types against whitelist
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- Limit response sizes
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- Rate limiting for expensive operations
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### 2. Data Privacy
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- No sensitive data in responses
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- Redact credentials from examples
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- Anonymize usage metrics
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- Clear audit logging
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## Migration Strategy
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### Phase 1: Shadow Mode
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- New tools run alongside old ones
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- Metrics collection to validate improvements
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- A/B testing with subset of users
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### Phase 2: Gradual Rollout
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- Feature flags for new tools
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- Progressive user migration
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- Monitoring and rollback capability
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### Phase 3: Deprecation
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- Mark old tools as deprecated
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- 3-month transition period
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- Migration guides and tooling
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## Future Considerations
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### 1. AI Model Integration
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- Property embeddings for semantic search
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- ML-based property importance ranking
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- Automated example generation
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- Predictive configuration
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### 2. Workflow Analysis
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- Learn from successful workflows
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- Identify common patterns
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- Suggest optimal configurations
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- Error pattern detection
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### 3. Real-time Assistance
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- WebSocket support for interactive configuration
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- Progressive property revelation
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- Context-aware suggestions
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- Collaborative editing support
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## Conclusion
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These technical decisions prioritize:
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1. **Immediate value delivery** through incremental improvements
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2. **AI-first design** optimizing for token efficiency
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3. **Performance** with strict budgets and caching
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4. **Reliability** through graceful degradation
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5. **Future flexibility** with extensible architecture
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The implementation follows a pragmatic approach that delivers quick wins while building toward a comprehensive solution. |