Memory Server MCP
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- AlicenseNot gradedqualityDmaintenanceProvides persistent memory storage for AI agents with full-text search, tagging, and importance levels, enabling agents to store and retrieve memories efficiently.MIT
- FlicenseBqualityDmaintenanceEnables persistent memory for AI systems by providing tools for episodic, semantic, and procedural data storage through a vector-and-graph-enhanced database. It allows models to maintain long-term continuity using similarity search, thematic clustering, and identity tracking.241-
- FlicenseAqualityNot gradedmaintenanceProvides long-term memory storage for AI assistants with semantic search, enabling persistent storage of preferences, decisions, and context with relationship tracking between memories.19-

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.1411 npmMIT
Oceanir Memoryofficial
FlicenseNot gradedqualityDmaintenanceProvides persistent long-term memory for AI coding agents by storing entities, relations, and observations across different sessions. It enables users to manage and query structured knowledge like coding preferences, project patterns, and technical solutions via a graph-based storage system.1-- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to store and retrieve persistent memories with a web management interface. Supports creating, searching, and managing memories through natural language commands or a visual web dashboard.28 npm1MIT
TDQS
Scored across 12 tools
Most tools have distinct purposes, but there is some overlap between 'find_related_memories' and 'search_by_relationship', as both involve relationship-based queries, which could cause confusion. Other tools like 'recall_memory' and 'get_linked_memories' are clearly differentiated, with the former retrieving a single memory and the latter focusing on linked connections.
All tool names follow a consistent snake_case pattern with clear verb_noun structures, such as 'delete_memory', 'save_memory', and 'search_memory_content'. This uniformity makes the tool set predictable and easy to navigate, with no deviations in naming conventions.
With 12 tools, the count is well-suited for a memory management server, covering core operations like save, recall, delete, search, and linking. Each tool serves a specific function without redundancy, making the set comprehensive yet manageable for its domain.
The tool set provides complete coverage for memory management, including CRUD operations (save, recall, delete, list), advanced features like linking, searching by content and relationships, and utility functions such as tag listing. There are no obvious gaps, supporting a full lifecycle from creation to complex queries.