ultimate-mcp-server
Version:
The definitive all-in-one Model Context Protocol server for AI-assisted coding across 30+ platforms
81 lines • 2.16 kB
TypeScript
/**
* Knowledge Graph Implementation
* Core graph structure and operations for cognitive memory
*/
import { CognitiveNode, CognitiveEdge, MemorySearchOptions, MemoryContext, CognitiveMemoryConfig } from './types.js';
import { EmbeddingProvider } from '../rag/embeddings.js';
export declare class KnowledgeGraphManager {
private graph;
private config;
private embeddingProvider?;
constructor(config?: CognitiveMemoryConfig);
initialize(embeddingProvider?: EmbeddingProvider): Promise<void>;
/**
* Add a node to the knowledge graph
*/
addNode(node: Omit<CognitiveNode, 'id' | 'createdAt' | 'updatedAt' | 'accessCount' | 'lastAccessed'>): Promise<CognitiveNode>;
/**
* Add an edge between nodes
*/
addEdge(edge: Omit<CognitiveEdge, 'id' | 'createdAt'>): Promise<CognitiveEdge>;
/**
* Search for nodes using semantic similarity
*/
search(options: MemorySearchOptions): Promise<MemoryContext>;
/**
* Get related nodes through graph traversal
*/
private getRelatedNodes;
/**
* Update node importance based on connections and usage
*/
private updateNodeImportance;
/**
* Prune least important nodes
*/
private pruneNodes;
/**
* Prune least important edges
*/
private pruneEdges;
/**
* Remove a node and its edges
*/
removeNode(nodeId: string): Promise<void>;
/**
* Remove an edge
*/
removeEdge(edgeId: string): Promise<void>;
/**
* Calculate cosine similarity between embeddings
*/
private cosineSimilarity;
/**
* Simple text similarity fallback
*/
private textSimilarity;
/**
* Calculate recency boost
*/
private recencyBoost;
/**
* Save graph to disk
*/
private saveToDisk;
/**
* Load graph from disk
*/
private loadFromDisk;
/**
* Get graph statistics
*/
getStats(): Record<string, any>;
/**
* Export graph for visualization
*/
exportForVisualization(): {
nodes: any[];
edges: any[];
};
}
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