Transform Claude's Hidden Memory Into Interactive Knowledge Graphs Universal tool to visualize any Claude user's memory.json in beautiful interactive graphs. Transform your Claude Memory MCP data into stunning interactive visualizations to see how your AI assistant's knowledge connects and evolves over time. Enterprise teams using Claude lack visibility into how their AI assistant accumulates and organizes institutional knowledge. Claude Memory Viz provides zero-configuration visualization that automatically finds memory files and displays 72 entities with 93 relationships in real-time force-directed layouts. Teams can filter by entity type, search across all data, and explore detailed connections through rich tooltips. The technical implementation supports Claude's standard NDJSON memory format, automatically detecting and color-coding entity types from personality profiles to technical tools. Node size reflects connection count, while adjustable physics parameters enable optimal spacing for large knowledge graphs. Built with Cytoscape.js for performance optimization. Built with the philosophy "Solve it once and for all," the tool works for any Claude user with zero configuration. The visualizer automatically searches common memory file locations, provides demo data fallback, and offers clear guidance when files aren't found. Integration requires just git clone and one command execution. This matters because AI memory has been invisible to users, creating trust and accountability gaps in enterprise AI deployment. When teams can visualize how their AI assistant organizes knowledge, they gain insights into decision-making patterns and can optimize their AI collaboration strategies. 👩‍💻https://lnkd.in/e__RQh_q | 10 comments on LinkedIn

Want to explore the Anthropic Transformer-Circuit's as a queryable graph? Wrote a script to import the graph json into Neo4j - code in Gist. https://lnkd.in/eT4NjQgY https://lnkd.in/e38TfQpF Next step - write directly from the circuit-tracer library to the graph db. https://lnkd.in/eVU_t6mS

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End to end solution for migrating CSV data into a Neo4j graph using an LLM for the data discovery and graph data modeling stages. - a-s-g93/neo4j-runway

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