This Elasticsearch-based knowledge graph implementation for MCP replaces the previous JSON file-based approach with a scalable, performant solution. It provides distributed storage for entities and relations, advanced search capabilities with fuzzy matching and relevancy ranking, and complete CRUD operations. The system tracks access patterns to prioritize recently viewed and important entities, simulating memory-like behavior where important, recent, and frequently accessed information rises to the top. Built with TypeScript and the Elasticsearch client, it includes tools for migration, management, and maintenance through a comprehensive admin CLI.
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Highlight AISearch the memory for specific information or entities. Parameters: query (string)
View details about a specific entity in memory. Parameters: entityName (string)
Back up your entire memory system to a specified file. Parameters: backupFile (string)
Create a new memory zone for organizing knowledge. Parameters: zoneName (string), description (string)
Import data into a specific memory zone from a JSON file. Parameters: dataFile (string), zoneName (string)
