mcp-automem
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kairnofficial
AlicenseNot gradedqualityAmaintenanceProvides AI assistants with a persistent knowledge graph and experience memory, featuring context-aware routing, progressive disclosure, decay-based forgetting, and automatic promotion of important knowledge. It offers 22 MCP tools for storing, recalling, connecting, and querying knowledge, experiences, preferences, and ideas.53 PyPI13MIT- AlicenseNot gradedqualityBmaintenanceA personal AI memory hub that stores and retrieves personal data from any MCP-enabled AI assistant, enabling persistent memory across conversations.5MIT
TDQS
Scored across 6 tools
Each tool has a clearly distinct primary action (health, store, recall, associate, update, delete). There is minor overlap between store_memory's supersede mode and update_memory since both can correct existing memories, but the descriptions explain when to use each, so misselection risk is low.
All tools follow a consistent snake_case verb_noun pattern: check_database_health, store_memory, recall_memory, associate_memories, update_memory, delete_memory. The naming is predictable and readable throughout.
Six tools is well-scoped for a memory service. Each tool earns its place by covering a distinct operation without excessive fragmentation.
The surface covers the full memory lifecycle: create/store, read/recall, update, delete, graph association, and health checking. Recall supports ID fetch, exhaustive tag enumeration, and ranked retrieval, leaving no obvious dead ends.