memorygraph
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Alternatives to memorygraph
No user-submitted related servers found.
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- AlicenseNot gradedqualityAmaintenanceProvides AI agents a shared long-term memory layer with evidence-backed, auditable claims, enabling persistent, explainable, and conflict-aware recall across sessions.212 PyPI7MIT
- AlicenseNot gradedqualityBmaintenanceProvides AI agents with long-term memory that tracks temporal validity and corrections, enabling context-aware retrieval of past facts via MCP tools.MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to store and retrieve typed facts with bi-temporal validity, supersede outdated information, and query what was true as of any past date.MIT
- AlicenseAqualityBmaintenanceEnables AI agents to maintain long-term, cross-session memory by extracting facts, reconciling state conflicts, and retrieving relevant memories via vector search.4MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to maintain persistent memory across sessions with verifiable source receipts, supporting explicit remember, recall, inspect, correct, and forget operations.1 npm31Apache 2.0

MemCell MCP Serverofficial
AlicenseNot gradedqualityCmaintenanceEnables AI agents to use persistent, adaptive cognitive memory by recalling relevant memories and principles before acting, storing durable facts and observations, and reporting outcomes to calibrate confidence over time.1Apache 2.0
TDQS
Scored across 5 tools
Each tool targets a distinct operation: explain (query graph), recall (retrieve observations), record (store), correct (update claims), forget (delete). No overlapping purposes, and descriptions clearly separate them.
All tool names are single lowercase verbs, creating a uniform and predictable pattern. This consistency makes it easy to infer the action each tool performs.
Five tools is well-scoped for a memory graph server, covering core operations without redundancy. Each tool addresses a necessary part of the memory lifecycle.
The set covers record, recall, correct, forget, and explain, which covers full CRUD-like operations on claims and observations. Minor gaps like explicit listing or bulk operations exist but are not critical for core usage.