Mem0 vs Zep vs LangMem vs MemoClaw: AI Agent Memory Comparison 2026

Your AI agent forgets everything between sessions. You know this. The question is which memory solution to pick — and honestly, the answer depends on what you're building.

This is a no-BS comparison of the four main options in 2026: Mem0, Zep, LangMem, and MemoClaw. We build MemoClaw, so we're biased — but we'll tell you where the others win.

TL;DR

Mem0

Website: mem0.ai · YC-backed · 50,000+ developers

Mem0 is the most well-known player in this space, and for good reason. They've built a solid managed platform with both an open-source self-hosted option and a cloud service.

What's good

• Mature ecosystem. Python and JS SDKs, integrations with OpenAI, LangGraph, CrewAI, Vercel AI SDK. If you're using a popular framework, Mem0 probably has an integration.
• Memory compression engine. Mem0 intelligently compresses chat history into optimized memory representations. They claim up to 80% prompt token reduction. That's real cost savings at scale.
• Graph memory. On Pro and above, you get a knowledge graph that links entities and relationships across conversations. This is powerful for complex use cases like customer support or healthcare.
• Self-hosting option. The open-source version lets you run Mem0 on your own infra. The managed platform adds scaling, observability, and compliance.
• Enterprise-ready. SOC 2, HIPAA, BYOK, on-prem deployment. If your compliance team needs checkboxes, Mem0 has them.
• MCP server. Universal AI integration through Model Context Protocol.

What's not great

• Pricing jumps are steep. Free tier gives you 10K memories and 1K retrieval calls/month. After that, it's $19/mo for 50K memories, then $249/mo for Pro. If you're a solo developer or small project, that $19→$249 jump is rough.
• Graph memory is paywalled. The most interesting feature requires Pro ($249/mo). On free/starter, you get basic vector memory only.
• API key management. Standard API key auth means you need to manage keys, rotate them, and deal with the usual key leakage risks.
• Can feel heavy. If all you want is "store this, recall that," the workspace/project/user hierarchy adds complexity you might not need.

Pricing

• Hobby (Free): 10K memories, 1K retrieval calls/mo
• Starter ($19/mo): 50K memories, 5K retrieval calls/mo
• Pro ($249/mo): Unlimited memories, 50K retrieval calls/mo, graph memory
• Enterprise: Custom

Zep

Website: getzep.com

Zep has repositioned itself as a "context engineering platform" — and that's not just marketing. It's fundamentally different from the others on this list.

What's good

• Temporal knowledge graph. This is Zep's killer feature. It doesn't just store memories; it builds a graph of entities, relationships, and facts that evolves over time. When facts change, old ones get invalidated. No other tool on this list handles temporal knowledge this well.
• Context assembly. Zep doesn't just retrieve memories — it assembles personalized context blocks optimized for your LLM. You get structured, token-efficient context, not just a list of memories.
• Business data ingestion. You can push JSON business data, not just chat messages. This makes Zep useful for enterprise apps where agents need to know about orders, accounts, or inventory.
• Custom entity types. Define your own entity and relationship models. If you're in healthcare, you can model patients, conditions, and treatments. Zep adapts to your domain.
• Three SDKs. Python, TypeScript, and Go. The Go SDK is a differentiator — most competitors skip it.
• Graphiti (open source). Zep's temporal knowledge graph framework is open source, so you can self-host the graph layer even without paying for Zep cloud.
• SOC 2 Type II and HIPAA BAA.

What's not great

• Complexity. Zep is the most complex option here. Episodes, facts, summaries, context templates, custom entity types — there's a lot to learn. If you just want to store and retrieve memories, Zep is overkill.
• Credit-based pricing is confusing. An "episode" is any data object you send, and objects over 350 bytes cost multiple credits. You need to do math to figure out your actual costs.
• No self-hosted option (cloud only). Graphiti is OSS, but the full Zep platform is cloud-only. If you need on-prem, you're limited to Graphiti.
• No free tier to speak of. 1,000 free credits/month with lower priority processing and rate limits. That's barely enough to prototype.
• Heavier integration. Zep wants to be your context layer, not just your memory store. That's great if you're all-in, but it means more buy-in upfront.

Pricing

• Free: 1K credits/mo (heavily rate-limited)
• Flex ($25/mo): 20K credits, auto-topup at $25/20K credits
• Enterprise: Custom (BYOK, BYOM, BYOC options)

LangMem

Website: langchain-ai.github.io/langmem

LangMem is different from the others — it's a library, not a service. Built by the LangChain team, it adds memory capabilities to LangGraph agents.

What's good

• Free and open source. pip install langmem and you're done. No API keys, no accounts, no monthly bills. If you're budget-constrained, this is hard to beat.
• Deep LangGraph integration. If you're already building with LangGraph, LangMem is the natural choice. It plugs directly into LangGraph's storage layer and works with create_react_agent out of the box.
• You own everything. Your data, your infra, your embeddings. No vendor lock-in, no data leaving your environment.
• Background memory manager. Automatically extracts, consolidates, and updates agent knowledge from conversations. The agent doesn't have to explicitly decide what to remember.
• Prompt refinement. LangMem can optimize agent behavior by refining prompts based on past interactions. This goes beyond simple memory storage.
• Flexible storage. Bring any storage backend — InMemoryStore for dev, AsyncPostgresStore for production, or implement your own.

What's not great

• LangGraph lock-in. LangMem is designed for LangGraph. If you're using a different framework (or no framework), you'll be fighting the library instead of using it.
• Python only. No JavaScript/TypeScript SDK. If your agent stack is in Node.js, LangMem isn't an option.
• You manage everything. Embeddings, vector storage, scaling, backups — it's all on you. That's the trade-off for "free."
• No semantic search service. You need to set up your own embedding pipeline and vector index. LangMem gives you the tools, but you wire the plumbing.
• No knowledge graph. LangMem stores memories as flat key-value items with vector search. No entity extraction, no relationship modeling.
• Documentation is thin. Compared to Mem0 and Zep, the docs are more sparse. You'll be reading source code.

Pricing

• Free (open source, MIT license)
• You pay for your own infra (Postgres, embeddings API, compute)

MemoClaw

Website: memoclaw.com · Docs: docs.memoclaw.com

Full disclosure: we make MemoClaw. We'll be honest about what we do and don't do.

What's good

• Dead-simple API. Two core operations: store and recall. That's it. No workspaces, no projects, no entity types. If you can make an HTTP request, you can use MemoClaw.
• No registration, no API keys. Your crypto wallet is your identity. Connect a wallet, get 1,000 free API calls. No sign-up forms, no email verification, no API key rotation.
• True pay-per-use. No monthly subscriptions. Store a memory for $0.001, recall for $0.001. You pay for what you use, when you use it. $1 = 1,000 memories. If your agent goes quiet for a month, you pay nothing.
• x402 payments. Pay with USDC on Base via the x402 protocol. Every request is a microtransaction. No invoices, no billing cycles.
• MCP server. npm install -g memoclaw-mcp for native tool access from any MCP-compatible agent.
• Importance scoring. Weight memories by importance (0-1). High-importance memories (like user corrections) rank higher in recall. Simple but effective.
• Namespaces. Isolate memories per project or context without managing multiple accounts.
• Works with any framework. It's just an HTTP API. OpenAI, LangChain, CrewAI, custom agents — doesn't matter.

What's not great (honestly)

• No knowledge graph. We do vector-based semantic search. If you need entity extraction, relationship modeling, or temporal knowledge graphs, use Zep or Mem0 Pro.
• No self-hosting. Cloud only (api.memoclaw.com). If you need on-prem, look at Mem0's OSS or LangMem.
• Crypto wallet required. After the free tier, you need USDC on Base to pay. If your team doesn't do crypto, this is a barrier. We know.
• OpenAI embeddings only. We use OpenAI's embedding model. You can't bring your own embedding provider.
• 8K character limit per memory. Not designed for large documents. If you need to store full documents, use a RAG solution.
• No memory compression. We store what you send. Mem0's automatic compression from chat history is a feature we don't have.
• Smaller ecosystem. We're newer and smaller than Mem0. Fewer integrations, smaller community.

Pricing

• Free: 1,000 API calls per wallet
• Pay-per-use: $0.001/store, $0.001/recall, $0.0005/list, $0.0001/delete
• No subscriptions. No tiers. No surprises.

Decision Matrix: Which One Should You Pick?

Pick Mem0 if:

• You want a mature, well-supported managed platform
• You need graph memory and can afford $249/mo
• Your team prefers traditional API key auth
• You want the self-hosting option as a fallback
• Enterprise compliance (SOC 2, HIPAA) is a hard requirement right now

Pick Zep if:

• Your app needs rich entity and relationship modeling
• You're building something where facts change over time (CRM, healthcare, e-commerce)
• You want structured context assembly, not just raw memory retrieval
• You're okay with higher complexity for more powerful features
• You need a Go SDK

Pick LangMem if:

• You're already building with LangGraph
• You want zero vendor dependencies
• Budget is the top constraint
• You need full control over your data and infrastructure
• You only need Python

Pick MemoClaw if:

• You want the simplest possible memory API
• You hate managing API keys and accounts
• You prefer pay-per-use over monthly subscriptions
• You're building with crypto-native infrastructure
• Your agent needs basic store/recall without graph complexity
• You're prototyping and want to start in 30 seconds

Feature Comparison Table

The Bottom Line

There's no single best option. The market has matured enough that each tool serves a different niche:

• Mem0 is the safe, well-rounded choice. Most features, most integrations, most mature. The pricing model is the main thing to evaluate — those monthly tiers can add up.
• Zep is the power tool. If your app needs to understand entities and relationships over time, nothing else comes close. But you're paying for that power in complexity and cost.
• LangMem is the developer's choice for LangGraph shops. Free, flexible, and you own everything. Just be ready to manage your own infrastructure.
• MemoClaw is the minimalist option. Simplest API, no accounts, pay only for what you use. We're not trying to be everything — just really good at store and recall.

Pick the one that matches your actual needs, not the one with the most features. An agent with simple, working memory beats an agent with a complex memory system that you never finish integrating.

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Last updated: February 2026. Pricing and features may change — check each provider's docs for the latest.

Disclosure: This article is published by the MemoClaw team. We've done our best to be accurate and fair. If we got something wrong, let us know.