mcp-memory
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- AlicenseNot gradedqualityDmaintenancePersistent memory MCP server for Claude Code. Store, search, and retrieve memories across sessions using hybrid vector + keyword search powered by SQLite, FTS5, and sqlite-vec.21 npm1MIT
- AlicenseNot gradedqualityDmaintenanceA secure vector-based memory server that provides persistent semantic memory for AI assistants using sqlite-vec and sentence-transformers. It enables semantic search and organization of coding experiences, solutions, and knowledge with features like auto-cleanup and deduplication.MIT
- AlicenseNot gradedqualityCmaintenanceA persistent memory server that stores and retrieves atomic coding insights like architectural decisions and debugging patterns for AI agents. It enables agents to maintain institutional knowledge across sessions using semantic search and local SQLite storage.8 npm11MIT
- AlicenseNot gradedqualityCmaintenanceProvides persistent local memory for AI assistants using SQLite and semantic search, enabling context-aware conversations.16 npmMIT
- AlicenseAqualityAmaintenancePersistent AI memory server with 3-layer hybrid search (vector + FTS5 + keyword), confidence scoring via Reciprocal Rank Fusion, episodic/profile memory, and 16 tools. Zero LLM dependency. Works standalone with Claude Desktop and Claude Code. MIT licensed.341,650 PyPI8MIT
- AlicenseNot gradedqualityAmaintenancePersistent AI memory server with 3-layer hybrid search (vector + FTS5 + keyword), confidence scoring via Reciprocal Rank Fusion, episodic/profile memory, and 16 tools. Zero LLM dependency. Works standalone with Claude Desktop and Claude Code. MIT licensed.3Business Source 1.1
TDQS
Scored across 11 tools
Each tool has a clearly distinct purpose with no significant overlap: entity/relation/observation operations are separated, search functions target different methods, and administrative tools like migrate are unique. The descriptions reinforce distinct boundaries, making misselection unlikely.
All tools follow a consistent verb_noun naming pattern (e.g., add_observations, create_entities, delete_relations), with no deviations in style or convention. This predictability aids agent understanding and tool selection.
With 11 tools, the set is well-scoped for a knowledge graph memory system, covering core operations (CRUD for entities, relations, observations), search capabilities, and administrative functions. Each tool earns its place without bloat.
The tool surface provides complete coverage for the knowledge graph domain: full CRUD for entities, relations, and observations; multiple search methods (by attribute, semantic); graph reading; and data migration. No obvious gaps exist for typical agent workflows.