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Provide persistent graph memory, semantic search, and traversal for AI agents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Graph-Mem MCP" yet — see the docs or source repo.
Save this repository’s modules, API dependencies, key constraints, and recent decisions into Graph-Mem, and link them so future development Q&A and code generation can reuse the memory.
Structured project memory nodes and relationships are created for semantic retrieval and contextual traversal later.
Search Graph-Mem for past discussions, design decisions, and related implementation files about the user permission model, then summarize the key changes in timeline order.
Relevant memories, linked files, and a decision summary are returned to quickly restore context.
Using Graph-Mem multi-hop traversal, analyze the new enterprise SSO login requirement and identify affected modules, data entities, test points, and potential risks.
An impact analysis is produced, showing connected components, risks, and the required test scope.
Provide persistent graph-memory storage and retrieval for LLM agents via MCP.
Build a semantic graph from project files for search, knowledge, and task management.
Provides persistent graph memory for LLMs with auto-linking and layered recall.
Build a project knowledge graph for code search, traversal, and Q&A.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Give AI assistants persistent knowledge graph memory across sessions and workflows.