Version: 1.0.0
Date: 2025-08-24
Systems: mcp-coaia-sequential-thinking v1.0+ ↔ coaia-memory v2.0.7+
This document defines the comprehensive bidirectional data flow architecture that enables seamless integration between Robert Fritz's SCCP (Structural Creative Cognitive Process) thinking methodology and structural tension charts in memory systems.
Sequential Thinking → Structural Memory: When SCCP-based thinking sessions reach readyForChartCreation status, they automatically generate structural tension charts with proper entity relationships, telescoping support, and pattern preservation.
mcp-coaia-sequential-thinking (Python FastMCP):
- SCCP-based ThoughtStage enum: DESIRED_OUTCOME, CURRENT_REALITY, ACTION_STEPS, PATTERN_RECOGNITION, CONCEPT_DETECTION
- ThoughtAnalyzer with readyForChartCreation detection
- Pattern type detection: advancing vs oscillating
- Hidden concept detection for limiting beliefs
- Structural tension strength analysis (0.0-1.0)
coaia-memory (TypeScript MCP):
- Structural tension chart creation (createStructuralTensionChart)
- Telescoping support (telescopeActionStep)
- Entity-relationship model with metadata
- Due date inheritance and distribution
- Chart completion tracking
┌─────────────────────────────────────────────────────────────────┐
│ BIDIRECTIONAL FLOW │
├─────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────┐ Integration ┌─────────────────┐ │
│ │ SEQUENTIAL │◄───── Bridge ─────►│ COAIA MEMORY │ │
│ │ THINKING │ │ (Charts) │ │
│ │ │ │ │ │
│ │ • SCCP Process │ Auto-Create │ • Chart Entities│ │
│ │ • Pattern Track │ ┌─────────────────►│ • Relationships │ │
│ │ • Observations │ │ │ • Telescoping │ │
│ │ │ │ Update Reality │ • Patterns │ │
│ │ ThoughtAnalyzer │ │ ◄─────────────── │ Progress Track │ │
│ │ • readyForChart │ │ │ │ │
│ │ • patternType │ │ Chart Feedback │ StructuralChart │ │
│ │ • tensionStr │ │ ◄─────────────── │ • Completion │ │
│ └─────────────────┘ │ └─────────────────┘ │
│ ▲ │ ▲ │
│ │ │ │ │
│ │ │ │ │
│ ┌─────────────────┐ │ ┌─────────────────────────────────┐ │
│ │ INTEGRATION │◄─┴──┤ DATA TRANSFORMATION │ │
│ │ BRIDGE │ │ & MAPPING LAYER │ │
│ │ │ │ │ │
│ │ • Auto-trigger │ │ • ThoughtStage → EntityType │ │
│ │ • Transform │ │ • Observations → Entities │ │
│ │ • Validate │ │ • Patterns → Relations │ │
│ │ • Sync │ │ • Timing → DueDates │ │
│ └─────────────────┘ └─────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
The Integration Bridge is the central coordinator that manages:
| Sequential Thinking | ↔ | Coaia Memory |
|---|---|---|
DESIRED_OUTCOME thoughts |
→ | desired_outcome entities |
CURRENT_REALITY thoughts |
→ | current_reality entities |
ACTION_STEPS thoughts |
→ | action_step entities |
| Session with all 3 stages | → | structural_tension_chart entity |
| Pattern analysis results | → | Entity metadata & relations |
| Hidden concepts detected | → | Observation annotations |
interface ChartFromThinking {
// Core Chart Data
chartId: string;
sourceSessionId: string;
// SCCP-derived entities
entities: {
chart: {
name: string;
entityType: 'structural_tension_chart';
observations: string[];
metadata: {
sourceSession: string;
patternType: 'advancing' | 'oscillating';
tensionStrength: number;
sccp: {
originalThoughts: ThoughtData[];
hiddenConcepts: string[];
strategicActions: number;
}
}
};
desiredOutcome: Entity;
currentReality: Entity;
actionSteps: Entity[];
};
// Relationship preservation
relations: Relation[];
// Integration metadata
integration: {
createdAt: string;
updatedAt: string;
syncStatus: 'active' | 'completed' | 'archived';
telescopingChains: string[];
}
}
# In ThoughtAnalyzer (sequential-thinking)
def analyze_chart_readiness(thoughts: List[ThoughtData]) -> Dict[str, Any]:
analysis = {
"readyForChartCreation": (
has_desired_outcome and
has_current_reality and
has_action_steps
),
"chartCreationData": {
"desiredOutcome": extract_outcome(thoughts),
"currentReality": extract_reality(thoughts),
"actionSteps": extract_actions(thoughts),
"patternType": detect_pattern_type(thoughts),
"tensionStrength": calculate_tension_strength(thoughts),
"hiddenConcepts": collect_hidden_concepts(thoughts),
"dueDate": infer_timeline(thoughts)
}
}
# Trigger integration bridge if ready
if analysis["readyForChartCreation"]:
integration_bridge.create_chart_from_thinking(
session_id=current_session_id,
chart_data=analysis["chartCreationData"],
thoughts=thoughts
)
return analysis
class IntegrationBridge {
constructor(
private sequentialThinking: SequentialThinkingClient,
private coaiaMemory: CoaiaMemoryClient
) {}
async createChartFromThinking(
sessionId: string,
chartData: ChartCreationData,
thoughts: ThoughtData[]
): Promise<ChartIntegrationResult> {
// Transform SCCP data to chart format
const transformedData = this.transformSCCPToChart(chartData, thoughts);
// Create structural tension chart
const chartResult = await this.coaiaMemory.createStructuralTensionChart(
transformedData.desiredOutcome,
transformedData.currentReality,
transformedData.dueDate,
transformedData.actionSteps
);
// Enhance with SCCP metadata
await this.enrichChartWithSCCPData(chartResult.chartId, {
patternType: chartData.patternType,
tensionStrength: chartData.tensionStrength,
hiddenConcepts: chartData.hiddenConcepts,
originalThoughts: thoughts,
sourceSession: sessionId
});
// Establish bidirectional linking
await this.createIntegrationLinks(sessionId, chartResult.chartId);
return {
chartId: chartResult.chartId,
sessionId,
integrationStatus: 'active',
syncedAt: new Date().toISOString()
};
}
private transformSCCPToChart(
chartData: ChartCreationData,
thoughts: ThoughtData[]
): TransformedChartData {
return {
desiredOutcome: this.consolidateThoughts(
thoughts.filter(t => t.stage === ThoughtStage.DESIRED_OUTCOME)
),
currentReality: this.consolidateThoughts(
thoughts.filter(t => t.stage === ThoughtStage.CURRENT_REALITY)
),
actionSteps: thoughts
.filter(t => t.stage === ThoughtStage.ACTION_STEPS)
.map(t => t.thought),
dueDate: chartData.dueDate || this.inferDueDateFromThoughts(thoughts)
};
}
}
// Chart completion flows back to thinking system
async onActionStepCompleted(
chartId: string,
actionStepName: string
): Promise<void> {
// Update chart completion
await this.coaiaMemory.markActionComplete(chartId, actionStepName);
// Flow completion back to reality
const updatedReality = await this.generateUpdatedReality(chartId);
// Sync back to sequential thinking if session active
const integration = await this.getIntegrationRecord(chartId);
if (integration.syncStatus === 'active') {
await this.sequentialThinking.updateSessionReality(
integration.sessionId,
updatedReality
);
}
}
graph TD
A[Original Action Step] --> B[Telescoping Trigger]
B --> C[Extract Action as New Outcome]
C --> D[Request Current Reality for Detail]
D --> E[Create Sub-Chart]
E --> F[Inherit Due Date & Metadata]
F --> G[Establish Parent-Child Relations]
G --> H[Preserve SCCP Pattern Chain]
H --> I[Enable Recursive Telescoping]
subgraph "SCCP Preservation"
J[Pattern Type Inheritance]
K[Tension Strength Calculation]
L[Hidden Concept Detection]
M[Strategic Action Classification]
end
E --> J
E --> K
E --> L
E --> M
async telescopeWithSCCP(
actionStepName: string,
newCurrentReality: string,
thinkingContext?: {
sessionId: string;
thoughts: ThoughtData[];
patternAnalysis: PatternAnalysis;
}
): Promise<TelescopingResult> {
// Standard telescoping
const result = await this.coaiaMemory.telescopeActionStep(
actionStepName,
newCurrentReality
);
// Enhance with SCCP data if available
if (thinkingContext) {
await this.preserveSCCPPatterns(result.chartId, {
parentPatternType: thinkingContext.patternAnalysis.patternType,
inheritedTensionStrength: thinkingContext.patternAnalysis.tensionStrength,
conceptChain: thinkingContext.patternAnalysis.hiddenConcepts,
thoughtLineage: thinkingContext.thoughts
});
}
return result;
}
When a sequential thinking session exhibits an advancing pattern:
When oscillating patterns are detected:
interface PatternTrackingSystem {
detectPatternEvolution(
chartId: string,
completionEvents: ActionCompletion[]
): PatternEvolution;
reinforceAdvancingPattern(
chartId: string,
successSequence: ActionCompletion[]
): Promise<void>;
interruptOscillatingPattern(
chartId: string,
oscillationIndicators: string[]
): Promise<InterventionPlan>;
trackPatternChain(
parentChart: string,
childChart: string,
telescopingEvent: TelescopingEvent
): Promise<void>;
}
# New method in ThoughtAnalyzer
def trigger_chart_creation(self, thoughts: List[ThoughtData]) -> Optional[str]:
"""Auto-create chart when thoughts are ready"""
if self.is_ready_for_chart_creation(thoughts):
return integration_bridge.create_chart_from_session(
session_thoughts=thoughts,
pattern_analysis=self.analyze_structural_tension(thoughts)
)
return None
// New methods in KnowledgeGraphManager
async updateThinkingSessionReality(
sessionId: string,
newRealityElements: string[]
): Promise<void> {
// Flow completed chart actions back to thinking current reality
}
async synchronizePatternEvolution(
chartId: string,
patternEvolution: PatternEvolution
): Promise<void> {
// Update thinking system with pattern changes
}
User: "I want to create a mobile app for habit tracking"
Sequential Thinking Session:
1. Desired Outcome: "Launch a habit tracking mobile app with 1000+ users"
2. Current Reality: "I have iOS development skills but no app published yet"
3. Action Steps: "Design UI mockups", "Build MVP", "App Store submission", "Marketing launch"
→ System detects readyForChartCreation = true
→ Auto-creates structural tension chart with inherited pattern analysis
→ Chart includes advancing pattern metadata and strategic action classification
User completes "Design UI mockups" → wants detail
→ System telescopes into sub-chart:
- Desired Outcome: "Complete professional UI mockups for habit tracker"
- Current Reality: "Have Figma skills and competitor research done"
- Inherits due date from parent action step
- Preserves advancing pattern type from parent session
- Maintains hidden concept tracking across hierarchy levels
This architecture ensures that Robert Fritz's SCCP methodology integrity is preserved while enabling powerful structural memory capabilities through seamless bidirectional data flow.