Agent Memory
Best AI Agent Memory Tools in 2026
Memory tools help agents preserve user facts, task state, preferences, and long-running context beyond a single prompt window.
Search intent
Last reviewed
June 23, 2026
Tools considered
14
Open source options
13
Definition
Agent memory is the layer that decides what an agent should remember, retrieve, update, and forget across turns, users, and tasks.
Use cases
- Personal assistants that need stable user preferences
- Support agents that need account and conversation history
- Research workflows where findings must survive between runs
Selection criteria
- Does it support user-level isolation and deletion?
- Can memories be inspected, edited, and evaluated?
- Does retrieval improve decisions without flooding the prompt?
Selection advice
Use a dedicated memory layer when remembering facts is part of the product contract; use plain RAG when the task is mostly document grounding.
Tool comparison snapshot
| Tool | Best for | Open source | Main tradeoff | Open |
|---|---|---|---|---|
| Mem0 | user memory | Yes | static document Q&A | Open |
| Zep | temporal memory | Yes | small prototypes that only need session history | Open |
| Honcho | user identity modeling | Yes | simple key-value memory | Open |
| OpenViking | filesystem-based context | Yes | managed cloud-only teams | Open |
| Hindsight | knowledge graph memory | Yes | simple vector-only retrieval | Open |
| Holographic | vector symbolic architectures | Yes | distributed production deployments | Open |
| RetainDB | hybrid retrieval | Yes | simple key-value caching | Open |
| ByteRover | pre-compressed extraction | Yes | general-purpose vector search | Open |