agent-memory
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Alternatives to agent-memory
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- AlicenseNot gradedqualityAmaintenanceProvides AI agents with persistent, human-like memory infrastructure via MCP, enabling them to store, search, summarize, and forget episodic, semantic, procedural, and working memories across sessions.1,099 npmMIT

artificial-memoryofficial
AlicenseNot gradedqualityAmaintenanceEnables AI agents to persist, recall, expand, trace, and inspect durable memories with provenance through MCP tools.MIT- FlicenseNot gradedqualityCmaintenanceProvides agents with a structured long-term memory pipeline, enabling recall, hybrid retrieval, and memory management operations through MCP tools.-
- FlicenseAqualityBmaintenanceShared fleet memory for AI agents — what one agent learns, the whole fleet knows. Nightly self-correction: stale facts rewritten in place, duplicates merged. Recall pushed into every prompt in supported coding agents. Self-hosted.8112-
- FlicenseAqualityCmaintenanceEnables LLM agents to persist, search, update, forget, summarize, and manage user cognitive memories through MCP tools.7-
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to store and semantically retrieve durable memories across sessions via MCP or REST, with tools for remembering, recalling, asking, updating, and forgetting memories.18 npmMIT
TDQS
Scored across 13 tools
Each tool maps to a distinct resource and action: long-term memory CRUD, working memory read/write/clear, review queue list/resolve, unified context assembly, transcript reading, and session-end orchestration. Even memory_context is clearly an orchestration layer over memory_search and memory_wm_read, not a competing implementation. The only mild overlap is transcript_read versus session_end log parsing, but one is read-only and the other is a write pipeline.
All tools share the memory_ prefix and snake_case, but the pattern varies slightly: base operations use verb-only suffixes like memory_search and memory_add, while subarea operations use noun_verb suffixes like memory_wm_read and memory_review_resolve. memory_context and memory_feedback are noun-oriented rather than strict verb_noun. Overall the convention is still predictable and readable.
13 tools is well-scoped for a memory server covering long-term memory, working memory, review queue, context assembly, transcript access, and session-end orchestration. Each tool has a distinct lifecycle purpose, and none feels redundant or missing as a surface-level feature.
The surface covers full CRUD for long-term memories, working-memory read/write/clear, review workflow, context assembly, and session-end archival/distillation. The review-gate blocked/acknowledge and session-end veto/force flows prevent dead ends. The only arguable gap is dedicated profile management, but profiles are exposed through memory_context and updatable via memory_add/memory_update.