MahoRAGa
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- FlicenseNot gradedqualityCmaintenanceProvides AI agents with persistent, local cross-session shared memory by combining vector semantic retrieval with knowledge graph relationships, and supports short/long-term memory management and local backups.-
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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.1414 npmMIT- AlicenseNot gradedqualityBmaintenanceEnables persistent, graph-based memory for AI agents, allowing them to store, traverse, and recall relationships between facts, decisions, and context across sessions for efficient reasoning and reduced token usage.MIT
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TDQS
Scored across 55 tools
Each tool targets a distinct entity and operation (e.g., add_artifact vs add_concept, get_session_details vs get_concept_details). There is no meaningful overlap; even similar search tools have different scopes (semantic vs tag-based).
Tool names follow a consistent verb_noun pattern (e.g., add_artifact, delete_session, get_daily_activity). Minor variations like 'list' vs 'get' are standard, and batch operations are uniformly prefixed. No mixing of conventions.
With 55 tools, the count far exceeds the typical well-scoped range. While the domain is broad, this many tools risks overwhelming agents and suggests insufficient consolidation or granularity.
The tool set covers CRUD and lifecycle operations for all major entities (artifacts, concepts, sessions, projects, errors, solutions). Minor gaps exist, such as no direct update or delete for individual errors, but workflows are supported via session deletion and event logging.