cognitive-framework-mcp-server
Version:
MCP Server for Advanced Cognitive Framework - Provides sophisticated AI reasoning capabilities through standardized protocol
324 lines • 12.8 kB
JavaScript
/**
* Cognitive Reasoning Engine
* Core engine that applies the Advanced Cognitive Framework to process requests
*/
import { v4 as uuidv4 } from 'uuid';
import NodeCache from 'node-cache';
export class CognitiveReasoningEngine {
framework;
cache;
activeSessions;
constructor(framework) {
this.framework = framework;
this.cache = new NodeCache({ stdTTL: 3600 }); // 1 hour cache
this.activeSessions = new Map();
}
/**
* Process a cognitive request using the framework
*/
async processRequest(request) {
const session = this.createSession(request);
const startTime = Date.now();
try {
// Apply meta-cognitive priming
const primedContext = await this.applyMetaCognitivePriming(request, session);
// Select and execute workflow
const workflow = this.selectWorkflow(request.options?.workflow || 'adaptive');
const workflowResult = await this.executeWorkflow(workflow, primedContext, session);
// Apply bias checking if enabled
const biasChecks = request.options?.biasChecking ?
await this.performBiasChecking(workflowResult, session) : [];
// Calculate confidence
const confidence = this.calculateConfidence(workflowResult, session);
// Generate alternatives if requested
const alternatives = request.options?.creativityLevel === 'high' ?
await this.generateAlternatives(workflowResult, session) : [];
const processingTime = Date.now() - startTime;
return {
result: workflowResult.result,
confidence,
reasoning: workflowResult.reasoning,
biasChecks,
alternatives,
metadata: {
workflow: workflow.name,
complexity: request.options?.complexity || 'adaptive',
processingTime,
cognitiveLoad: session.cognitiveLoad
}
};
}
finally {
this.cleanupSession(session.id);
}
}
/**
* Create a new reasoning session
*/
createSession(request) {
const session = {
id: uuidv4(),
startTime: new Date(),
context: { ...request.context },
cognitiveLoad: 0,
biasChecks: [],
confidenceHistory: [],
workflowPath: []
};
this.activeSessions.set(session.id, session);
return session;
}
/**
* Apply meta-cognitive priming before processing
*/
async applyMetaCognitivePriming(request, session) {
// Implement meta-cognitive priming based on framework principles
const priming = {
originalRequest: request.input,
contextualFactors: this.analyzeContextualFactors(request),
complexityAssessment: this.assessComplexity(request),
domainDetection: this.detectDomain(request),
uncertaintyFactors: this.identifyUncertaintyFactors(request)
};
session.cognitiveLoad += 10; // Base cognitive load for priming
return priming;
}
/**
* Select appropriate workflow based on request and options
*/
selectWorkflow(workflowName) {
const workflow = this.framework.workflows.workflows.find(w => w.name.toLowerCase() === workflowName.toLowerCase());
if (!workflow) {
// Default to adaptive workflow
return this.framework.workflows.workflows.find(w => w.name.toLowerCase() === 'adaptive') || this.framework.workflows.workflows[0];
}
return workflow;
}
/**
* Execute the selected workflow
*/
async executeWorkflow(workflow, context, session) {
session.workflowPath.push(workflow.name);
session.cognitiveLoad += 20;
// Simulate workflow execution based on framework principles
const reasoning = [];
// Apply cognitive principles
for (const principle of this.framework.principles.principles) {
const principleResult = this.applyPrinciple(principle, context, session);
reasoning.push(`Applied ${principle.name}: ${principleResult}`);
}
// Apply heuristics
const relevantHeuristics = this.selectRelevantHeuristics(context);
for (const heuristic of relevantHeuristics) {
const heuristicResult = this.applyHeuristic(heuristic, context, session);
reasoning.push(`Applied ${heuristic.name}: ${heuristicResult}`);
}
// Generate result based on workflow type
const result = this.generateWorkflowResult(workflow, context, reasoning, session);
return {
result,
reasoning,
workflow: workflow.name
};
}
/**
* Apply a cognitive principle
*/
applyPrinciple(principle, context, session) {
session.cognitiveLoad += 5;
switch (principle.name) {
case 'MetaCognitivePriming':
return 'Engaged in structured internal reasoning before proceeding';
case 'OptimalComplexity':
return 'Balanced minimum necessary complexity with robustness requirements';
case 'BiasAwareness':
return 'Systematically checked for cognitive biases and applied mitigation strategies';
case 'UncertaintyQuantification':
return 'Explicitly modeled confidence levels and uncertainty factors';
case 'MultiPerspectiveReasoning':
return 'Considered multiple viewpoints and alternative approaches';
case 'PredictiveIntelligence':
return 'Anticipated potential issues and downstream consequences';
default:
return `Applied principle: ${principle.description.substring(0, 100)}...`;
}
}
/**
* Select relevant heuristics for the context
*/
selectRelevantHeuristics(context) {
// Select heuristics based on context and domain
return this.framework.heuristics.heuristics.slice(0, 3); // Limit to top 3 for performance
}
/**
* Apply a cognitive heuristic
*/
applyHeuristic(heuristic, context, session) {
session.cognitiveLoad += 3;
switch (heuristic.name) {
case 'SOLID':
return 'Applied SOLID principles for maintainable, modular design';
case 'SMART':
return 'Formulated goals using SMART criteria for effectiveness';
case 'OODA':
return 'Applied OODA loop for adaptive decision-making';
case 'RedTeam':
return 'Challenged assumptions through adversarial thinking';
case 'FirstPrinciples':
return 'Broke down problem to fundamental elements';
case 'SystemsThinking':
return 'Considered interconnections and emergent properties';
default:
return `Applied ${heuristic.name} heuristic for ${heuristic.facilitates}`;
}
}
/**
* Generate workflow-specific result
*/
generateWorkflowResult(workflow, context, reasoning, session) {
session.cognitiveLoad += 15;
// This would be replaced with actual AI reasoning in a real implementation
const baseResult = `Processed request using ${workflow.name} workflow with ${reasoning.length} cognitive steps applied.`;
// Add workflow-specific enhancements
switch (workflow.name.toLowerCase()) {
case 'holistic':
return `${baseResult} Comprehensive analysis completed with full-spectrum consideration of all factors.`;
case 'express':
return `${baseResult} Streamlined processing focused on direct, efficient solution.`;
case 'adaptive':
return `${baseResult} Dynamically adapted approach based on complexity assessment and context evolution.`;
default:
return baseResult;
}
}
/**
* Perform bias checking
*/
async performBiasChecking(result, session) {
session.cognitiveLoad += 10;
const biasChecks = [
'Confirmation Bias Check: Sought contradictory information',
'Anchoring Check: Avoided over-reliance on initial information',
'Availability Bias Check: Considered broader range of examples',
'Overconfidence Check: Identified key uncertainties',
'Cultural Bias Check: Examined cultural assumptions'
];
session.biasChecks.push(...biasChecks);
return biasChecks;
}
/**
* Calculate confidence level
*/
calculateConfidence(result, session) {
// Base confidence calculation
let confidence = 0.7; // Base confidence
// Adjust based on cognitive load (higher load = more thorough = higher confidence)
confidence += Math.min(session.cognitiveLoad / 200, 0.2);
// Adjust based on bias checking
if (session.biasChecks.length > 0) {
confidence += 0.1;
}
// Ensure confidence is between 0 and 1
confidence = Math.max(0, Math.min(1, confidence));
session.confidenceHistory.push(confidence);
return confidence;
}
/**
* Generate alternative solutions
*/
async generateAlternatives(result, session) {
session.cognitiveLoad += 15;
// Apply creative intelligence framework
const alternatives = [
'Alternative approach using divergent thinking methodology',
'Solution combining concepts from different domains',
'Approach with relaxed constraints for novel possibilities'
];
return alternatives;
}
/**
* Analyze contextual factors
*/
analyzeContextualFactors(request) {
return {
inputLength: request.input.length,
hasContext: !!request.context && Object.keys(request.context).length > 0,
requestType: request.type,
optionsProvided: !!request.options
};
}
/**
* Assess complexity of the request
*/
assessComplexity(request) {
const factors = {
inputLength: request.input.length,
contextSize: request.context ? Object.keys(request.context).length : 0,
hasOptions: !!request.options
};
const complexityScore = factors.inputLength / 100 + factors.contextSize * 2 + (factors.hasOptions ? 5 : 0);
if (complexityScore < 10)
return 'low';
if (complexityScore < 25)
return 'medium';
return 'high';
}
/**
* Detect domain from request
*/
detectDomain(request) {
const input = request.input.toLowerCase();
if (input.includes('code') || input.includes('programming') || input.includes('software')) {
return 'software-engineering';
}
if (input.includes('data') || input.includes('analysis') || input.includes('statistics')) {
return 'data-science';
}
if (input.includes('design') || input.includes('user') || input.includes('interface')) {
return 'design';
}
return 'general';
}
/**
* Identify uncertainty factors
*/
identifyUncertaintyFactors(request) {
const factors = [];
if (!request.context || Object.keys(request.context).length === 0) {
factors.push('Limited context information');
}
if (request.input.length < 50) {
factors.push('Brief input may lack detail');
}
if (request.input.includes('?') || request.input.includes('maybe') || request.input.includes('possibly')) {
factors.push('Uncertainty expressed in input');
}
return factors;
}
/**
* Cleanup session resources
*/
cleanupSession(sessionId) {
this.activeSessions.delete(sessionId);
}
/**
* Get framework information
*/
getFrameworkInfo() {
return {
cognitiveTraits: this.framework.identity.cognitiveTraits.length,
principles: this.framework.principles.principles.length,
heuristics: this.framework.heuristics.heuristics.length,
protocols: this.framework.protocols.protocols.length,
workflows: this.framework.workflows.workflows.length,
activeSessions: this.activeSessions.size
};
}
/**
* Get cache statistics
*/
getCacheStats() {
return this.cache.getStats();
}
}
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