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Build a personal knowledge graph from ChatGPT chats for on-demand code assistant search.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "chatgpt-kg" yet — see the docs or source repo.
Connect to chatgpt-kg and search my indexed ChatGPT conversations for discussions about “Neo4j schema design” and “MCP tool integration”. Summarize the key conclusions and cite the source conversations.
Relevant conversation snippets, topic links, and a concise summary with source references.
Use chatgpt-kg to analyze my past conversations about “RAG, vector databases, and knowledge graphs”. Identify connections, repeated questions, and conclusions I have already formed.
A topic relationship overview, repeated discussion points, and reusable summaries of prior understanding.
Search chatgpt-kg for my previous chats about “Claude Code workflow optimization” and extract practical advice, command patterns, and cautions relevant to my current project.
A task-ready summary of prior experience with traceable conversation evidence.
Automatically extract, merge, and query learned CS knowledge as a graph.
Turn unstructured text into a searchable knowledge graph memory system.
Give LLMs persistent knowledge graph memory with semantic retrieval and contextual recall.
Build and query vector knowledge graphs with semantic search and graph management.
Ingest documents into Neo4j to build and query a knowledge graph.
Provide pre-structured knowledge graphs for AI agents to improve RAG accuracy.