Category
Agent Memory Tools For Persistent Context
Agent memory covers the tools and layers that let agents retain useful context across sessions, tasks, and longer workflows. This part of the stack matters once an application needs more than chat history. The agent may need durable recall of user preferences, workspace knowledge, prior steps, or evolving context that should influence future decisions.
Who This Category Is For
- Developers building longer-running agent systems
- Teams that need persistent context
- Builders comparing memory-native platforms with lighter memory layers
Selection Criteria
- clear memory-layer role inside the stack
- persistent-context usefulness in real workflows
- fit with surrounding frameworks and production architecture
- enough differentiation between platform-style memory and infrastructure-style memory
- operational simplicity relative to the value memory adds
Featured Tools
This block is curated, not auto-sorted. It is meant to route broad category intent toward the strongest current anchors.
Letta
Stateful agent platform for building AI agents with persistent memory, tools, and long-running context across conversations.
Deployment: Cloud / Self hosted / Local
Pricing: Mixed
Source: Open source
Zep
Context engineering platform that assembles memory and business context for AI agents with low-latency retrieval and managed graph workflows.
Deployment: Cloud / Self hosted
Pricing: Freemium
Source: Closed source
Graphiti
Open-source framework for building temporally-aware knowledge graphs that give AI agents long-term recall over changing data.
Deployment: Self hosted / Local
Pricing: Open Source
Source: Open source
Mem0
Universal memory layer for AI agents that provides persistent, contextual memory across sessions and workflows.
Deployment: Cloud / Self hosted
Pricing: Mixed
Source: Open source
Related Compare Pages
These pages move readers from category-level discovery into a concrete head-to-head choice.