Memory Nexus MCP
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- AlicenseAqualityDmaintenanceProvides persistent semantic memory with semantic search, knowledge graphs, and Intelligence Packs for AI agents, enabling memory recall by meaning and session continuity.1038 npmMIT

Memsolus MCP Serverofficial
AlicenseAqualityDmaintenanceProvides persistent long-term memory for AI agents through semantic search and automated knowledge graph extraction. It enables agents to store, recall, and reason over facts, preferences, and relationships across multiple conversations and sessions.147 npmMIT- AlicenseNot gradedqualityDmaintenanceEnables AI agents to store, search, and recall semantic memories with three memory types (semantic, episodic, procedural) and auto-consolidation, compounding intelligence over time.7 npmMIT

RushDB MCP Serverofficial
AlicenseNot gradedqualityCmaintenanceEnables AI agents to gain persistent, structured memory that is semantically searchable and graph-traversable, allowing them to store and query records and relationships without managing embeddings or schemas.64 npmApache 2.0- AlicenseNot gradedqualityCmaintenanceEnables AI agents to store, recall, update, delete, and analyze persistent memories with semantic search, decay, and anomaly retrieval across hosted, self-hosted, or fully local storage modes.44 npm22MIT
- FlicenseNot gradedqualityDmaintenanceProvides AI agents with persistent, searchable memory that survives across conversations using semantic search, temporal versioning, and smart organization. Enables long-term context retention and cross-session continuity for AI assistants.14-
TDQS
Scored across 10 tools
Most tools have clearly distinct purposes (remember, recall, forget, connect), but recall, context, and awaken all serve retrieval-like functions and could be confused at session start. The descriptions help differentiate them, but there is slight overlap.
Naming follows no consistent pattern: single-word verbs (remember, recall, connect), nouns (stats, context), and verb_noun combinations (list_hats, wear_hat) are mixed. This makes the tool set feel less predictable than a uniform convention.
Ten tools is well within the ideal range for a memory system, covering core operations, session lifecycle, and the hat feature without unnecessary bloat. Each tool serves a distinct function.
The toolset provides good coverage for storing, retrieving, linking, and forgetting memories, plus session lifecycle and hat management. Missing an explicit update/modify operation for memories, but agents can likely work around via remember, and the overall surface is solid.