AI agent memory is the missing layer in modern AI workflows. Here are the best tools in 2026, ranked for different use cases — with real pricing, architecture breakdowns, and recommendations.
Best overall (free + local + MCP): Squish. Best managed cloud: Mem0. Best consumer/personal: SuperMemory. Best graph memory: Zep. Best ultra-lightweight local: Engram. Best open-source agent OS: Letta (MemGPT). Best LangChain integration: LangMem. Best graph+RAG: Cognee.
Squish is a local-first memory runtime for AI agents. Free for local use (MIT, unlimited), optional cloud from $9/mo. 18 MCP tools, 39 ops/sec, belief extraction, memory decay, semantic search. Works with Claude Code, Cursor, Codex, ChatGPT, OpenCode, and any MCP client. Cross-tool memory, team sharing via cloud sync. Open source, self-hostable. Best for: developers using Claude Code, Cursor, Codex, or ChatGPT who want persistent cross-session memory. Anyone comparing against Mem0 ($249/mo) who wants a free local alternative. Pricing: Free local (unlimited), Cloud free (2K req/mo), Solo $9/mo (10K), Pro $29/mo (50K), Team $99/mo (200K).
Mem0 is a managed cloud memory service for AI agents. It provides semantic memory storage, retrieval, and personalization without self-hosting. Mem0 Pro starts at $249/mo. Requires Qdrant for vector storage. Cloud-only — no local option. Best for: teams who want a fully managed cloud service and don't want to self-host. Teams already using Qdrant. Pricing: Hobby free (10K memories/mo), Starter $19/mo, Pro $249/mo, Enterprise custom. Note: Mem0 charges per add/retrieval, not per request — pricing model differs from Squish. Weaknesses: $249/mo Pro is expensive for individual developers. Cloud-only means no offline use. Requires Qdrant infrastructure. Not MCP-native (REST API).
SuperMemory is a consumer-focused AI memory app. Token-based pricing with a free tier. Designed for individuals who want personal AI memory — not for developers building agent workflows. No MCP integration. Standalone app. Best for: non-technical consumers who want a simple personal memory app. Weaknesses: Not developer-first. No MCP support. Token-based pricing. Not self-hostable. Not designed for AI agent workflows or team sharing.
Zep is a cloud-first graph-based memory service for AI assistants. It provides temporal graph memory with entity and relationship tracking. Pricing starts at $40/mo for individuals and $249/mo for teams, with enterprise options at $1,250+/yr. Partially open source (BSL license). Best for: enterprise use cases that need graph-based temporal memory. Teams that need managed infrastructure with enterprise features. Weaknesses: Cloud-first — limited self-hosting. $1,250+/yr for enterprise is expensive. BSL license (not MIT). Not MCP-native (REST API). More complex than what most individual developers need.
Engram is a free, ultra-lightweight local memory tool. Uses SQLite FTS5 for search. Free with a 30KB cap per memory. Local-only — no cloud sync. Simple setup. Best for: users who need a tiny local memory for a single project, under 30KB. Ultra-lightweight needs. Weaknesses: 30KB cap is very limiting for serious use. No cloud sync. No MCP integration. No belief extraction or decay. Not suitable for cross-tool or team memory.
Letta (formerly MemGPT) is an open-source agent operating system with stateful memory management. It manages in-context memory within agent sessions. Open-source, self-hostable. Different category from Squish — it's an agent framework, not a memory runtime. Best for: researchers and developers building stateful agent systems who want in-context memory management. Weaknesses: Different category — not a drop-in memory runtime. Complex setup. In-context memory (session-scoped) vs persistent storage (Squish). Not MCP-native. Less suitable for simple cross-session memory needs.
LangMem is an open-source memory module in the LangChain ecosystem (MIT). It provides memory primitives for LangChain agents. Best for developers already using LangChain who want memory integrated into their existing workflow. Best for: LangChain users who want memory as part of their existing stack. Weaknesses: Limited to LangChain ecosystem. Less mature than Squish or Mem0. Smaller community. Not a standalone runtime. Not MCP-native.
Cognee is an open-source graph+RAG memory system (GPL). It combines graph memory with retrieval-augmented generation. Python-first. Good for use cases that need both graph relationships and RAG-based retrieval. Best for: Python developers building complex memory systems that need both graph and RAG. Weaknesses: GPL license (more restrictive than MIT). Python-first (less suitable for Node.js/TypeScript stacks). More complex than most developers need. Not MCP-native.
Tool | License | Local | Cloud | MCP | Price | Best for Squish | MIT | Yes | Optional | 18 tools | Free + from $9/mo | Developers, AI agents Mem0 | Closed | No | Yes | REST API | $19-$249/mo | Managed cloud SuperMemory | Closed | No | Yes | No | Token-based | Consumers Zep | BSL | Limited | Yes | REST API | $40-$1,250+/yr | Graph memory, enterprise Engram | MIT | Yes | No | No | Free (30KB cap) | Ultra-lightweight local Letta | Open-source | Yes | Self-host | No | Free (hosting costs) | Agent OS LangMem | MIT | Yes | Optional | No | Free | LangChain users Cognee | GPL | Yes | Self-host | No | Free (hosting costs) | Graph+RAG, Python
Q: What is the best free AI memory tool? A: Squish. It's free for local use (MIT, unlimited), open-source, and has 18 MCP tools. Engram is also free but has a 30KB cap. Q: Is Mem0 worth it in 2026? A: Mem0 Pro at $249/mo is expensive for individual developers. For teams who want a fully managed cloud service, it may be worth it. For most developers, Squish gives you more for $0 locally. Q: Which AI memory tool works with Claude Code? A: Squish has native MCP support and works with Claude Code out of the box. Install with npm i -g squish-memory && squish install. Mem0 and Zep use REST APIs and require additional integration. Q: Can I use multiple AI memory tools together? A: Yes, but it adds complexity. Most developers pick one tool that fits their use case. Squish covers the same capabilities as Mem0 (semantic search, cloud sync, team collaboration) plus MCP native support, belief extraction, and memory decay — at a lower cost. Q: What is the best open-source AI memory tool? A: Squish (MIT, local-first, MCP-native), Engram (MIT, SQLite FTS5, 30KB cap), and Letta (open-source agent OS) are the top open-source options. Squish is the most complete for developer use cases.