Graphiti-Memory MCP Server
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- AlicenseAqualityCmaintenanceEnables AI agents to store, retrieve, and connect information in a Neo4j graph database as persistent memory, with semantic relationships, natural language search, and temporal tracking across conversations.944 npm70MIT
- FlicenseNot gradedqualityDmaintenanceEnables storage and retrieval of knowledge in a graph database format, allowing users to create, update, search, and delete entities and relationships in a Neo4j-powered knowledge graph through natural language.5-
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to build and query temporally-aware knowledge graphs from conversations and data. Supports adding episodes, searching entities and facts, and maintaining persistent memory across interactions.10Apache 2.0
- AlicenseNot gradedqualityDmaintenanceProvides persistent memory capabilities through Neo4j graph database integration, allowing storage and retrieval of interconnected knowledge with complex relationships between entities. Enables long-term retention and querying of information across multiple conversations through graph-based memory management.1MIT
- FlicenseNot gradedqualityCmaintenanceEnables ingesting documents or text to extract entities and relationships via LLM, storing them in Neo4j, and searching or retrieving episodes.-
- AlicenseNot gradedqualityDmaintenanceProvides persistent memory for Claude by implementing a local knowledge graph to store and retrieve entities, relations, and observations. This enables long-term information retention and personalization across different chat sessions.114,646 npm-
TDQS
Scored across 8 tools
Most tools have distinct purposes, such as add_memory for adding, clear_graph for clearing, and search_memory_facts for searching facts. However, get_entity_edge and search_memory_nodes could be slightly ambiguous since both involve retrieving entity-related information, but their descriptions clarify the difference (specific vs. search).
The naming follows a consistent verb_noun pattern with snake_case throughout, such as add_memory and delete_episode. There are minor deviations like get_entity_edge using 'entity_edge' instead of a more uniform term like 'fact', but overall the pattern is clear and predictable.
With 8 tools, the count is well-scoped for a memory/knowledge graph server, covering core operations like add, delete, get, search, and clear. Each tool serves a distinct function without bloat, making it manageable and purposeful for the domain.
The tool set provides good coverage for a knowledge graph domain, including add, delete, get, and search operations for episodes and entities. A minor gap is the lack of update tools for modifying existing memories or entities, but agents can work around this by deleting and re-adding, and core workflows are supported.