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Build and explore a neuroscience-inspired knowledge graph for search and reasoning.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-engram" yet — see the docs or source repo.
Search the knowledge graph for nodes related to "working memory". List the most relevant concepts, their connections, and a brief description of each node.
A list of relevant nodes, their relationships, and short explanations for quick topic understanding.
Starting from "hippocampus", traverse multi-hop paths to "long-term memory consolidation", showing intermediate nodes in order and explaining each relationship.
One or more traversal paths with structured explanations for each step in the graph.
Using temporal information in the graph, organize the event sequence around "learning-sleep-memory strengthening" and summarize possible causal or temporal patterns.
A time-ordered event chain plus a summary of potential temporal patterns or reasoning conclusions.
Search local Claude Code history with hybrid semantic and keyword retrieval.
Give AI clients persistent memory with hybrid search and knowledge graph retrieval.
Give AI tools a personal semantic memory layer for storing and recalling information.
Give AI assistants persistent memory, adaptive recall, and graph-based knowledge retrieval.
Ingest documents into Neo4j to build and query a knowledge graph.
Semantically search and enrich org-roam knowledge graphs with local LLM support.