Enables AI assistants to interact with Neo4j graph databases through natural language, supporting Cypher queries, schema management, data manipulation, and graph algorithms.
Enables LLMs to interact with Neo4j graph databases using natural language to execute Cypher queries and introspect database schemas. It supports both read and write operations for local, Docker, and cloud-based instances like Neo4j Aura.
Enables storage and retrieval of knowledge in a graph database format, allowing users to create, update, search, and delete entities and relationships in a Neo4j-powered knowledge graph through natural language.
Enables LLMs to build and explore a cognitive neuroscience-inspired knowledge graph with SQLite, supporting search, graph traversal, temporal sequences, and structured reasoning.
Enables storing and querying memories in a Neo4j knowledge graph with automatic entity extraction. Supports adding episodes, searching entities and relationships, and managing graph data through natural language.
Enables AI agents to build, populate, and search knowledge graphs by providing tools for entity extraction, relationship mapping, and graph traversal. It manages the underlying database infrastructure so users can create searchable knowledge bases from text through natural language commands.