# AI Integration Patterns
Advanced patterns for integrating Claude Code with the Session Management MCP server. This guide shows how to leverage the memory system, workflow intelligence, and session management for optimal AI-assisted development.
## 🎯 Core Integration Patterns
### Pattern 1: Context-Aware Development Workflow
**Use Case**: Starting work on a feature with full historical context
```typescript
// 1. Initialize session with project analysis
const initResult = await mcp_tool("mcp__session-buddy__start", {
working_directory: "/path/to/project"
})
// 2. Search for related previous work
const context = await mcp_tool("mcp__session-buddy__quick_search", {
query: "user authentication implementation OAuth JWT",
limit: 5,
min_score: 0.75,
include_related_projects: true
})
// 3. Use context to inform implementation approach
if (context.success && context.results.length > 0) {
console.log("Found relevant context from previous work:")
context.results.forEach(result => {
console.log(`- ${result.project}: ${result.content.substring(0, 100)}...`)
console.log(` Similarity: ${result.similarity_score}, Date: ${result.timestamp}`)
})
}
// 4. Implement feature with historical insights
// ... development work ...
// 5. Store new insights for future use
await mcp_tool("mcp__session-buddy__store_reflection", {
content: "Implemented OAuth 2.0 with PKCE extension for SPA security. Key insight: Use state parameter for CSRF protection and nonce for replay attack prevention.",
tags: ["oauth", "security", "spa", "authentication", "pkce"]
})
```
**Benefits**:
- Avoids repeating past mistakes
- Builds on successful patterns
- Creates cumulative learning across sessions
______________________________________________________________________
### Pattern 2: Progressive Context Discovery
**Use Case**: Exploring a codebase or problem space before implementation
```typescript
// Stage 1: Quick assessment
const quickCheck = await mcp_tool("mcp__session-buddy__quick_search", {
query: "Redis caching implementation patterns",
project: "current"
})
console.log(`Found ${quickCheck.total_count} related conversations`)
if (quickCheck.has_more && quickCheck.total_count > 3) {
// Stage 2: Detailed exploration
const detailed = await mcp_tool("mcp__session-buddy__quick_search", {
query: "Redis caching implementation patterns",
limit: 10,
min_score: 0.7
})
// Stage 3: Concept-based exploration
const concepts = await mcp_tool("mcp__session-buddy__search_by_concept", {
concept: "caching strategies",
include_files: true,
limit: 8
})
// Stage 4: File-specific context if specific files identified
if (concepts.results.some(r => r.files?.includes("cache.py"))) {
const fileContext = await mcp_tool("mcp__session-buddy__search_by_file", {
file_path: "cache.py",
limit: 5
})
}
}
```
**Benefits**:
- Efficient token usage with progressive depth
- Comprehensive context without overwhelming information
- Smart filtering based on relevance
______________________________________________________________________
### Pattern 3: Quality-Driven Development Cycle
**Use Case**: Maintaining high code quality throughout development
```typescript
// Development cycle with quality monitoring
class QualityDrivenWorkflow {
private sessionStarted = false
private lastCheckpoint = Date.now()
private readonly checkpointInterval = 45 * 60 * 1000 // 45 minutes
async startSession(workingDirectory: string) {
const result = await mcp_tool("mcp__session-buddy__start", {
working_directory: workingDirectory
})
if (result.success) {
this.sessionStarted = true
console.log(`Session started with quality baseline: ${result.project_context.health_score}/100`)
// Set up periodic quality checks
this.scheduleQualityCheck()
}
return result
}
async performQualityCheck() {
if (!this.sessionStarted) return
const checkpoint = await mcp_tool("mcp__session-buddy__checkpoint", {})
if (checkpoint.success) {
console.log(`Current quality score: ${checkpoint.quality_score.overall}/100`)
// Act on quality insights
if (checkpoint.quality_score.overall < 75) {
console.log("⚠️ Quality declining. Recommendations:")
checkpoint.recommendations.forEach(rec => console.log(` - ${rec}`))
}
// Auto-apply workflow optimizations
if (checkpoint.optimization_suggestions.length > 0) {
console.log("🔄 Workflow optimizations available:")
checkpoint.optimization_suggestions.forEach(opt => console.log(` - ${opt}`))
}
this.lastCheckpoint = Date.now()
}
}
private scheduleQualityCheck() {
setTimeout(() => {
this.performQualityCheck()
this.scheduleQualityCheck() // Reschedule
}, this.checkpointInterval)
}
async endSession() {
const result = await mcp_tool("mcp__session-buddy__end", {})
if (result.success) {
console.log(`Session ended. Final quality: ${result.final_quality_score}/100`)
console.log(`Handoff file: ${result.handoff_file_path}`)
console.log("Key learnings captured:")
result.learning_captured.insights.forEach(insight =>
console.log(` - ${insight}`)
)
}
return result
}
}
```
**Benefits**:
- Continuous quality monitoring
- Automated workflow optimization
- Comprehensive session documentation
______________________________________________________________________
### Pattern 4: Cross-Project Knowledge Mining
**Use Case**: Applying solutions from other projects to current work
```typescript
async function crossProjectSolution(problemDescription: string, currentProject: string) {
// 1. Search across all projects for solutions
const globalSearch = await mcp_tool("mcp__session-buddy__quick_search", {
query: problemDescription,
limit: 15,
min_score: 0.7
// No project filter - search everything
})
// 2. Analyze solutions by project to identify patterns
const projectSolutions = new Map()
globalSearch.results.forEach(result => {
if (!projectSolutions.has(result.project)) {
projectSolutions.set(result.project, [])
}
projectSolutions.get(result.project).push(result)
})
// 3. Get concept-level insights across projects
const conceptSearch = await mcp_tool("mcp__session-buddy__search_by_concept", {
concept: extractConcepts(problemDescription),
include_files: true,
limit: 10
})
// 4. Synthesize cross-project patterns
const patterns = synthesizePatterns(projectSolutions, conceptSearch)
// 5. Store meta-insight about cross-project patterns
await mcp_tool("mcp__session-buddy__store_reflection", {
content: `Cross-project analysis for "${problemDescription}": ${patterns.summary}.
Common patterns: ${patterns.commonApproaches.join(", ")}.
Recommended approach for ${currentProject}: ${patterns.recommendation}`,
tags: ["cross-project", "patterns", "architecture", ...patterns.concepts]
})
return patterns
}
function extractConcepts(description: string): string {
// Extract key technical concepts from problem description
// Implementation would use NLP or keyword extraction
return description.toLowerCase()
.match(/\b(authentication|caching|database|api|security|performance|testing)\b/g)?.[0] || "general"
}
function synthesizePatterns(projectSolutions: Map, conceptSearch: any) {
// Analyze solutions across projects to identify common patterns
return {
summary: "Analysis of solutions across projects",
commonApproaches: ["pattern1", "pattern2"],
recommendation: "Based on similar contexts, recommend approach X",
concepts: ["concept1", "concept2"]
}
}
```
**Benefits**:
- Leverages knowledge from entire development history
- Identifies successful patterns across different contexts
- Prevents reinventing solutions already discovered
______________________________________________________________________
### Pattern 5: Intelligent Error Recovery
**Use Case**: Learning from past debugging sessions to solve current issues
```typescript
async function intelligentErrorRecovery(errorMessage: string, stackTrace: string, context: any) {
// 1. Search for similar errors in past conversations
const errorSearch = await mcp_tool("mcp__session-buddy__quick_search", {
query: `error "${errorMessage}" debugging solution`,
limit: 10,
min_score: 0.6 // Lower threshold for error patterns
})
// 2. Search by error concepts and patterns
const conceptSearch = await mcp_tool("mcp__session-buddy__search_by_concept", {
concept: "error handling debugging",
include_files: true,
limit: 8
})
// 3. Analyze stack trace for file-specific context
const relevantFiles = extractFilesFromStackTrace(stackTrace)
const fileContexts = await Promise.all(
relevantFiles.map(file =>
mcp_tool("mcp__session-buddy__search_by_file", {
file_path: file,
limit: 5
})
)
)
// 4. Synthesize debugging strategy
const debuggingStrategy = synthesizeDebuggingApproach(
errorSearch.results,
conceptSearch.results,
fileContexts.flatMap(fc => fc.results)
)
// 5. Store successful resolution for future use
const resolutionTracker = {
async recordResolution(solution: string, effectiveness: number) {
await mcp_tool("mcp__session-buddy__store_reflection", {
content: `Error Resolution: "${errorMessage}" - Solution: ${solution}. Effectiveness: ${effectiveness}/10. Context: ${JSON.stringify(context)}`,
tags: ["debugging", "error-resolution", "troubleshooting", getErrorCategory(errorMessage)]
})
}
}
return { debuggingStrategy, resolutionTracker }
}
function extractFilesFromStackTrace(stackTrace: string): string[] {
// Extract file paths from stack trace
const filePattern = /(?:at|in) ([^\s]+\.(py|js|ts|jsx|tsx|java|go|rs)):(\d+)/g
const files = []
let match
while ((match = filePattern.exec(stackTrace)) !== null) {
files.push(match[1])
}
return [...new Set(files)] // Remove duplicates
}
function getErrorCategory(errorMessage: string): string {
const categories = {
'database': /database|sql|connection|query/i,
'authentication': /auth|login|token|permission/i,
'network': /network|http|request|response|timeout/i,
'validation': /validation|invalid|required|format/i,
'performance': /performance|slow|timeout|memory/i
}
for (const [category, pattern] of Object.entries(categories)) {
if (pattern.test(errorMessage)) return category
}
return 'general'
}
```
**Benefits**:
- Faster error resolution using historical solutions
- Pattern recognition across error types
- Building debugging expertise over time
______________________________________________________________________
### Pattern 6: Session Continuity and Handoff
**Use Case**: Seamlessly continuing work across sessions and team members
```typescript
class SessionContinuityManager {
async prepareHandoff(sessionSummary: string, nextSteps: string[]) {
// 1. Perform final checkpoint
const checkpoint = await mcp_tool("mcp__session-buddy__checkpoint", {})
// 2. Store critical session insights
await mcp_tool("mcp__session-buddy__store_reflection", {
content: `Session Handoff - ${sessionSummary}. Current state: ${checkpoint.quality_score.overall}/100 quality. Next steps: ${nextSteps.join(", ")}`,
tags: ["session-handoff", "continuity", "next-steps"]
})
// 3. Create comprehensive context package
const contextPackage = await this.createContextPackage(sessionSummary)
// 4. End session with handoff documentation
const endResult = await mcp_tool("mcp__session-buddy__end", {})
return {
handoff_file: endResult.handoff_file_path,
context_package: contextPackage,
final_quality: endResult.final_quality_score,
learnings: endResult.learning_captured
}
}
async resumeFromHandoff(handoffInfo: any) {
// 1. Initialize new session
const initResult = await mcp_tool("mcp__session-buddy__start", {})
// 2. Load previous session context
const previousContext = await mcp_tool("mcp__session-buddy__quick_search", {
query: "session-handoff continuity next-steps",
limit: 5,
min_score: 0.8
})
// 3. Get file-specific context for current work
if (handoffInfo.active_files) {
const fileContexts = await Promise.all(
handoffInfo.active_files.map(file =>
mcp_tool("mcp__session-buddy__search_by_file", {
file_path: file,
limit: 3
})
)
)
}
return {
session_initialized: initResult.success,
previous_context: previousContext.results,
recommendations: this.generateResumptionRecommendations(previousContext)
}
}
private async createContextPackage(sessionSummary: string) {
// Gather comprehensive session context
const recentWork = await mcp_tool("mcp__session-buddy__quick_search", {
query: sessionSummary,
limit: 10,
min_score: 0.7
})
const stats = await mcp_tool("mcp__session-buddy__reflection_stats", {})
return {
recent_work: recentWork.results,
knowledge_base_stats: stats,
session_summary: sessionSummary
}
}
private generateResumptionRecommendations(previousContext: any): string[] {
// Analyze previous context to suggest resumption strategies
return [
"Review handoff documentation created in previous session",
"Continue work on identified next steps",
"Check for any changes in project dependencies",
"Validate previous session's quality improvements"
]
}
}
```
**Benefits**:
- Seamless session transitions
- Preserved context across breaks
- Efficient team collaboration
## 🔧 Advanced Integration Techniques
### Memory-Optimized Search Strategies
```typescript
class SmartSearchStrategy {
async executeOptimalSearch(query: string, context: SearchContext) {
// Progressive search with token optimization
const strategy = this.determineSearchStrategy(query, context)
switch (strategy) {
case 'focused':
return this.focusedSearch(query, context)
case 'exploratory':
return this.exploratorySearch(query, context)
case 'comprehensive':
return this.comprehensiveSearch(query, context)
default:
return this.adaptiveSearch(query, context)
}
}
private async focusedSearch(query: string, context: SearchContext) {
// High similarity, specific project, recent timeframe
return await mcp_tool("mcp__session-buddy__quick_search", {
query,
limit: 5,
min_score: 0.85,
project: context.currentProject
})
}
private async exploratorySearch(query: string, context: SearchContext) {
// Lower similarity, cross-project, concept-based
const semantic = await mcp_tool("mcp__session-buddy__quick_search", {
query,
limit: 8,
min_score: 0.6
})
const conceptual = await mcp_tool("mcp__session-buddy__search_by_concept", {
concept: this.extractMainConcept(query),
include_files: true,
limit: 6
})
return this.combineResults(semantic, conceptual)
}
private determineSearchStrategy(query: string, context: SearchContext): SearchStrategy {
// Analyze query characteristics to determine optimal strategy
const queryComplexity = this.analyzeQueryComplexity(query)
const contextDepth = context.availableMemory
const urgency = context.urgency || 'normal'
if (queryComplexity === 'simple' && urgency === 'high') return 'focused'
if (queryComplexity === 'complex' && contextDepth === 'rich') return 'comprehensive'
return 'exploratory'
}
}
interface SearchContext {
currentProject: string
availableMemory: 'minimal' | 'moderate' | 'rich'
urgency?: 'low' | 'normal' | 'high'
previousSearches?: string[]
}
```
### Workflow Integration Hooks
```typescript
// Integration with existing development workflows
class WorkflowIntegration {
// Git hook integration
async onPreCommit() {
const checkpoint = await mcp_tool("mcp__session-buddy__checkpoint", {})
if (checkpoint.quality_score.overall < 70) {
console.warn("⚠️ Quality score low before commit. Consider reviewing:")
checkpoint.recommendations.forEach(rec => console.warn(` - ${rec}`))
// Optionally block commit or just warn
return { allow: true, warnings: checkpoint.recommendations }
}
return { allow: true }
}
// CI/CD integration
async onDeploymentStart(environment: string) {
// Store deployment context
await mcp_tool("mcp__session-buddy__store_reflection", {
content: `Deployment to ${environment} initiated. Pre-deployment quality score: ${await this.getCurrentQualityScore()}`,
tags: ["deployment", environment, "quality-gate"]
})
// Search for previous deployment issues
return await mcp_tool("mcp__session-buddy__quick_search", {
query: `deployment ${environment} issues problems`,
limit: 5,
min_score: 0.7
})
}
// IDE integration hooks
async onFileOpen(filePath: string) {
// Get context for newly opened file
return await mcp_tool("mcp__session-buddy__search_by_file", {
file_path: filePath,
limit: 3
})
}
async onError(errorInfo: ErrorInfo) {
// Automatic error context gathering
return await this.intelligentErrorRecovery(
errorInfo.message,
errorInfo.stackTrace,
errorInfo.context
)
}
}
```
## 🎯 Best Practices
### Session Management
1. **Always initialize**: Use `init` at session start
1. **Regular checkpoints**: Every 30-45 minutes during active development
1. **Clean endings**: Always use `end` for proper cleanup
1. **Context before action**: Search before implementing new features
### Memory Optimization
1. **Progressive search**: Start with `quick_search`, then expand
1. **Appropriate similarity**: 0.8+ for precise, 0.6+ for exploration
1. **Tag consistently**: Use meaningful, consistent tags for reflections
1. **Store insights immediately**: Capture solutions while fresh
### Search Strategy
1. **Layer searches**: Combine semantic, concept, and file-based searches
1. **Use project filtering**: For large knowledge bases
1. **Time-aware queries**: Consider recency in search terms
1. **Iterate and refine**: Use search results to refine subsequent searches
### Quality Integration
1. **Monitor trends**: Track quality scores over time
1. **Act on recommendations**: Implement suggested optimizations
1. **Document decisions**: Store reasoning behind architectural choices
1. **Learn from mistakes**: Capture and analyze failure patterns
______________________________________________________________________
**Next Steps**:
- **[Architecture Guide](../developer/ARCHITECTURE.md)** - Deep dive into system design
- **[Configuration Reference](../user/CONFIGURATION.md)** - Advanced setup options
