/**
* Psycho-Symbolic Reasoning MCP Tools
* Integrates hybrid AI reasoning combining symbolic logic with psychological patterns
*/
import { Tool } from '@modelcontextprotocol/sdk/types.js';
import * as fs from 'fs';
import * as path from 'path';
import { fileURLToPath } from 'url';
const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);
// Knowledge graph storage
const knowledgeGraph = new Map<string, any>();
const reasoningPaths = new Map<string, any>();
export class PsychoSymbolicTools {
getTools(): Tool[] {
return [
{
name: 'psycho_symbolic_reason',
description: 'Perform psycho-symbolic reasoning on a query',
inputSchema: {
type: 'object',
properties: {
query: {
type: 'string',
description: 'The reasoning query'
},
context: {
type: 'object',
description: 'Additional context for reasoning',
default: {}
},
depth: {
type: 'number',
description: 'Maximum reasoning depth',
default: 5,
minimum: 1,
maximum: 10
}
},
required: ['query']
}
},
{
name: 'knowledge_graph_query',
description: 'Query the knowledge graph',
inputSchema: {
type: 'object',
properties: {
query: {
type: 'string',
description: 'Graph query in natural language'
},
filters: {
type: 'object',
description: 'Query filters'
},
limit: {
type: 'number',
description: 'Maximum results',
default: 10,
minimum: 1,
maximum: 100
}
},
required: ['query']
}
},
{
name: 'add_knowledge',
description: 'Add new knowledge to the graph',
inputSchema: {
type: 'object',
properties: {
subject: {
type: 'string',
description: 'Subject entity'
},
predicate: {
type: 'string',
description: 'Relationship type'
},
object: {
type: 'string',
description: 'Object entity'
},
metadata: {
type: 'object',
description: 'Additional metadata'
}
},
required: ['subject', 'predicate', 'object']
}
},
{
name: 'analyze_reasoning_path',
description: 'Analyze and explain a reasoning path',
inputSchema: {
type: 'object',
properties: {
query: {
type: 'string',
description: 'Original query'
},
showSteps: {
type: 'boolean',
description: 'Show detailed steps',
default: true
},
includeConfidence: {
type: 'boolean',
description: 'Include confidence scores',
default: true
}
},
required: ['query']
}
},
{
name: 'detect_contradictions',
description: 'Detect logical contradictions in knowledge',
inputSchema: {
type: 'object',
properties: {
domain: {
type: 'string',
description: 'Knowledge domain to check'
},
depth: {
type: 'number',
description: 'Analysis depth',
default: 3
}
}
}
},
{
name: 'cognitive_pattern_analysis',
description: 'Analyze cognitive patterns in reasoning',
inputSchema: {
type: 'object',
properties: {
pattern: {
type: 'string',
enum: ['convergent', 'divergent', 'lateral', 'systems', 'critical', 'abstract'],
description: 'Cognitive pattern type'
},
data: {
type: 'object',
description: 'Data to analyze'
}
},
required: ['pattern']
}
}
];
}
async handleToolCall(name: string, args: any): Promise<any> {
switch (name) {
case 'psycho_symbolic_reason':
return this.performReasoning(args.query, args.context, args.depth);
case 'knowledge_graph_query':
return this.queryKnowledgeGraph(args.query, args.filters, args.limit);
case 'add_knowledge':
return this.addKnowledge(args.subject, args.predicate, args.object, args.metadata);
case 'analyze_reasoning_path':
return this.analyzeReasoningPath(args.query, args.showSteps, args.includeConfidence);
case 'detect_contradictions':
return this.detectContradictions(args.domain, args.depth);
case 'cognitive_pattern_analysis':
return this.analyzeCognitivePattern(args.pattern, args.data);
default:
throw new Error(`Unknown psycho-symbolic tool: ${name}`);
}
}
private async performReasoning(query: string, context: any = {}, depth: number = 5): Promise<any> {
const reasoningSteps = [];
let currentDepth = 0;
let currentQuery = query;
const visited = new Set<string>();
// Initialize reasoning with psychological patterns
const cognitivePatterns = this.identifyCognitivePattern(query);
reasoningSteps.push({
type: 'pattern_identification',
patterns: cognitivePatterns,
confidence: 0.85
});
// Symbolic logic processing
while (currentDepth < depth) {
if (visited.has(currentQuery)) break;
visited.add(currentQuery);
// Extract logical components
const logicalComponents = this.extractLogicalComponents(currentQuery);
reasoningSteps.push({
type: 'logical_decomposition',
components: logicalComponents,
depth: currentDepth
});
// Apply inference rules
const inferences = this.applyInferenceRules(logicalComponents, context);
reasoningSteps.push({
type: 'inference',
rules: inferences.rules,
conclusions: inferences.conclusions
});
// Check for contradictions
const contradictions = this.checkContradictions(inferences.conclusions);
if (contradictions.length > 0) {
reasoningSteps.push({
type: 'contradiction_resolution',
contradictions,
resolution: this.resolveContradictions(contradictions)
});
}
// Generate next query level
const nextQuery = this.generateNextQuery(inferences.conclusions);
if (!nextQuery) break;
currentQuery = nextQuery;
currentDepth++;
}
// Synthesize final answer
const synthesis = this.synthesizeAnswer(reasoningSteps, query);
// Store reasoning path
reasoningPaths.set(query, {
steps: reasoningSteps,
synthesis,
timestamp: Date.now()
});
return {
answer: synthesis.answer,
confidence: synthesis.confidence,
reasoning: reasoningSteps,
patterns: cognitivePatterns,
depth: currentDepth
};
}
private identifyCognitivePattern(query: string): string[] {
const patterns = [];
const lowerQuery = query.toLowerCase();
if (lowerQuery.includes('why') || lowerQuery.includes('cause')) {
patterns.push('causal');
}
if (lowerQuery.includes('how') || lowerQuery.includes('process')) {
patterns.push('procedural');
}
if (lowerQuery.includes('what if') || lowerQuery.includes('suppose')) {
patterns.push('hypothetical');
}
if (lowerQuery.includes('compare') || lowerQuery.includes('difference')) {
patterns.push('comparative');
}
if (lowerQuery.includes('all') || lowerQuery.includes('every')) {
patterns.push('universal');
}
if (lowerQuery.includes('some') || lowerQuery.includes('exist')) {
patterns.push('existential');
}
if (patterns.length === 0) {
patterns.push('exploratory');
}
return patterns;
}
private extractLogicalComponents(query: string): any {
return {
predicates: this.extractPredicates(query),
quantifiers: this.extractQuantifiers(query),
operators: this.extractLogicalOperators(query),
entities: this.extractEntities(query)
};
}
private extractPredicates(text: string): string[] {
// Simple predicate extraction
const predicates = [];
const words = text.split(/\s+/);
for (let i = 0; i < words.length - 1; i++) {
if (words[i + 1] && /^(is|are|was|were|has|have|had)$/i.test(words[i])) {
predicates.push(`${words[i]} ${words[i + 1]}`);
}
}
return predicates;
}
private extractQuantifiers(text: string): string[] {
const quantifiers = [];
const patterns = /\b(all|every|some|none|any|most|few|many)\b/gi;
const matches = text.match(patterns);
return matches || [];
}
private extractLogicalOperators(text: string): string[] {
const operators = [];
const patterns = /\b(and|or|not|if|then|implies|equals)\b/gi;
const matches = text.match(patterns);
return matches || [];
}
private extractEntities(text: string): string[] {
// Simple entity extraction (would use NER in production)
const words = text.split(/\s+/);
return words.filter(word =>
word.length > 3 &&
/^[A-Z]/.test(word) &&
!['What', 'When', 'Where', 'Why', 'How', 'Who'].includes(word)
);
}
private applyInferenceRules(components: any, context: any): any {
const rules = [];
const conclusions = [];
// Modus Ponens
if (components.operators.includes('if') && components.operators.includes('then')) {
rules.push('modus_ponens');
conclusions.push('conditional_inference');
}
// Universal Instantiation
if (components.quantifiers.some(q => /^(all|every)$/i.test(q))) {
rules.push('universal_instantiation');
conclusions.push('specific_instance');
}
// Existential Generalization
if (components.quantifiers.some(q => /^(some|exist)$/i.test(q))) {
rules.push('existential_generalization');
conclusions.push('existence_claim');
}
return { rules, conclusions };
}
private checkContradictions(conclusions: string[]): any[] {
const contradictions = [];
// Check for logical contradictions
for (let i = 0; i < conclusions.length; i++) {
for (let j = i + 1; j < conclusions.length; j++) {
if (this.areContradictory(conclusions[i], conclusions[j])) {
contradictions.push({
statement1: conclusions[i],
statement2: conclusions[j],
type: 'logical'
});
}
}
}
return contradictions;
}
private areContradictory(s1: string, s2: string): boolean {
// Simplified contradiction detection
return (s1.includes('not') && s2 === s1.replace('not', '').trim()) ||
(s2.includes('not') && s1 === s2.replace('not', '').trim());
}
private resolveContradictions(contradictions: any[]): any {
return {
method: 'consistency_restoration',
resolution: contradictions.map(c => ({
original: c,
resolved: 'requires_context_disambiguation'
}))
};
}
private generateNextQuery(conclusions: string[]): string | null {
if (conclusions.length === 0) return null;
// Generate follow-up query based on conclusions
const lastConclusion = conclusions[conclusions.length - 1];
if (lastConclusion === 'conditional_inference') {
return 'What are the conditions?';
} else if (lastConclusion === 'existence_claim') {
return 'What examples exist?';
}
return null;
}
private synthesizeAnswer(steps: any[], originalQuery: string): any {
const insights = [];
let confidence = 0.5;
for (const step of steps) {
if (step.type === 'inference') {
insights.push(...step.conclusions);
confidence += 0.1;
}
if (step.type === 'pattern_identification') {
confidence += step.confidence * 0.2;
}
}
confidence = Math.min(confidence, 1.0);
return {
answer: `Based on ${steps.length} reasoning steps, ${insights.join(', ')}`,
confidence,
insights
};
}
private async queryKnowledgeGraph(query: string, filters: any = {}, limit: number = 10): Promise<any> {
const results = [];
// Search through knowledge graph
for (const [key, value] of knowledgeGraph.entries()) {
if (this.matchesQuery(value, query, filters)) {
results.push({
id: key,
...value
});
if (results.length >= limit) break;
}
}
return {
query,
results,
total: results.length
};
}
private matchesQuery(item: any, query: string, filters: any): boolean {
const queryLower = query.toLowerCase();
// Check if any field contains the query
const itemStr = JSON.stringify(item).toLowerCase();
if (!itemStr.includes(queryLower)) return false;
// Apply filters
for (const [key, value] of Object.entries(filters)) {
if (item[key] !== value) return false;
}
return true;
}
private async addKnowledge(subject: string, predicate: string, object: string, metadata: any = {}): Promise<any> {
const id = `${subject}-${predicate}-${object}-${Date.now()}`;
const knowledge = {
subject,
predicate,
object,
metadata,
timestamp: Date.now()
};
knowledgeGraph.set(id, knowledge);
return {
id,
knowledge,
status: 'added'
};
}
private async analyzeReasoningPath(query: string, showSteps: boolean = true, includeConfidence: boolean = true): Promise<any> {
const path = reasoningPaths.get(query);
if (!path) {
// Generate new reasoning path
const result = await this.performReasoning(query, {}, 5);
return {
query,
path: showSteps ? result.reasoning : null,
confidence: includeConfidence ? result.confidence : null,
answer: result.answer
};
}
return {
query,
path: showSteps ? path.steps : null,
confidence: includeConfidence ? path.synthesis.confidence : null,
answer: path.synthesis.answer
};
}
private async detectContradictions(domain?: string, depth: number = 3): Promise<any> {
const contradictions = [];
const items = [];
// Collect items from domain
for (const [key, value] of knowledgeGraph.entries()) {
if (!domain || value.metadata?.domain === domain) {
items.push(value);
}
}
// Check for contradictions
for (let i = 0; i < items.length; i++) {
for (let j = i + 1; j < items.length; j++) {
const contradiction = this.detectItemContradiction(items[i], items[j]);
if (contradiction) {
contradictions.push(contradiction);
}
}
}
return {
domain,
contradictions,
total: contradictions.length
};
}
private detectItemContradiction(item1: any, item2: any): any | null {
// Check for direct contradictions
if (item1.subject === item2.subject &&
item1.predicate === item2.predicate &&
item1.object !== item2.object) {
return {
type: 'direct',
item1,
item2,
conflict: 'conflicting_objects'
};
}
// Check for inverse relationships
if (item1.subject === item2.object &&
item1.object === item2.subject &&
this.areInversePredicates(item1.predicate, item2.predicate)) {
return {
type: 'inverse',
item1,
item2,
conflict: 'inverse_relationship'
};
}
return null;
}
private areInversePredicates(p1: string, p2: string): boolean {
const inversePairs = [
['causes', 'prevents'],
['increases', 'decreases'],
['supports', 'opposes'],
['enables', 'blocks']
];
for (const [a, b] of inversePairs) {
if ((p1 === a && p2 === b) || (p1 === b && p2 === a)) {
return true;
}
}
return false;
}
private async analyzeCognitivePattern(pattern: string, data: any = {}): Promise<any> {
const analysis = {
pattern,
characteristics: [],
strengths: [],
limitations: [],
applications: []
};
switch (pattern) {
case 'convergent':
analysis.characteristics = ['focused', 'analytical', 'logical'];
analysis.strengths = ['problem-solving', 'decision-making'];
analysis.limitations = ['limited_creativity', 'single_solution_focus'];
analysis.applications = ['mathematics', 'engineering', 'diagnosis'];
break;
case 'divergent':
analysis.characteristics = ['creative', 'exploratory', 'flexible'];
analysis.strengths = ['innovation', 'multiple_solutions'];
analysis.limitations = ['lack_of_focus', 'difficulty_concluding'];
analysis.applications = ['brainstorming', 'art', 'research'];
break;
case 'lateral':
analysis.characteristics = ['indirect', 'creative', 'unconventional'];
analysis.strengths = ['breakthrough_thinking', 'novel_solutions'];
analysis.limitations = ['unpredictable', 'hard_to_validate'];
analysis.applications = ['innovation', 'problem_reframing'];
break;
case 'systems':
analysis.characteristics = ['holistic', 'interconnected', 'complex'];
analysis.strengths = ['comprehensive_understanding', 'emergence_recognition'];
analysis.limitations = ['complexity', 'computational_intensity'];
analysis.applications = ['ecology', 'economics', 'organizations'];
break;
case 'critical':
analysis.characteristics = ['analytical', 'evaluative', 'skeptical'];
analysis.strengths = ['error_detection', 'quality_assurance'];
analysis.limitations = ['negativity_bias', 'analysis_paralysis'];
analysis.applications = ['review', 'validation', 'debugging'];
break;
case 'abstract':
analysis.characteristics = ['conceptual', 'theoretical', 'generalizable'];
analysis.strengths = ['pattern_recognition', 'transferable_knowledge'];
analysis.limitations = ['practical_application', 'concrete_examples'];
analysis.applications = ['theory', 'mathematics', 'philosophy'];
break;
}
// Apply pattern to data if provided
if (data && Object.keys(data).length > 0) {
(analysis as any).application = this.applyPatternToData(pattern, data);
}
return analysis;
}
private applyPatternToData(pattern: string, data: any): any {
// Simplified pattern application
return {
pattern,
data_summary: `Analyzed ${Object.keys(data).length} data points`,
insights: [`${pattern} thinking applied to data`],
recommendations: [`Consider ${pattern} approach for this problem`]
};
}
}
export default PsychoSymbolicTools;