LangMem
LangMem: A focused LangGraph and CrewAI toolkit for adding structured, persistent agent memory. Ranked #34 of 34 in AI Agent Memory Tools by our editors (4.8/10); pricing: Free plan; best for langGraph users needing open-source memory primitives.
At a glance
- Editor score4.8 / 10
- PricingFree plan
- Best forLangGraph users needing open-source memory primitives
- Free planYes
- Paid fromNone
- Semantic memoryYes
- Founded2025 · San Francisco, United States
- Facts checked13 Oct 2026
Where it wins
- Covers semantic, episodic and structured profile memory
- Supports background consolidation, search and metadata filtering
- Integrates with LangGraph and CrewAI using persistent storage options
Where it doesn't
- Python SDK focus limits the listed language choice to one
- Support is provided through documentation only
- Hosting and storage costs vary by deployment and database choice
Our verdict on LangMem
LangMem is an open-source Python SDK from LangChain for adding long-term memory to AI agents. It extracts and updates semantic facts, user profiles and episodic experiences from conversations, while also supporting procedural prompt optimization. Developers can use stateless functional APIs with their own storage or connect memory tools and managers to LangGraph’s storage layer. The package is suited to solo developers through enterprise teams building agents around LangGraph, CrewAI or custom workflows.
LangMem is distributed under the MIT license with a free plan and an open-source pricing model. There are no paid tiers described for the SDK itself; infrastructure economics depend on deployment and storage choices. The deployment options include cloud and self-hosted environments, and persistence can use stores such as Postgres. Integration coverage is intentionally centered on LangGraph and CrewAI, making the SDK a natural fit for those ecosystems rather than a broad, multi-platform memory layer.
Its strongest technical distinction is the breadth of memory operations in one toolkit. Semantic memory extraction and collection management handle durable facts, episodic extraction supports experience replay, and structured profile memory stores user attributes. Agents can search memories semantically, filter by metadata and work within namespaces. A background memory manager separates extraction and consolidation from the active path, while prompt optimization targets procedural behavior. Teams that want these primitives and are comfortable managing their own deployment should consider LangMem; buyers needing a wider integration footprint, more than one listed SDK language or support channels beyond documentation may prefer an alternative.
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LangMem pricing
LangMem fact sheet
| Free plan | Yes |
|---|---|
| Paid from | None |
| Semantic memory | Yes |
| Episodic memory | Yes |
| User/profile memory | Yes |
| Graph-based memory | Not verified |
| Deployment options | Both |
| SDK languages | 1 |
| Retention policy | Not verified |
| Deployment | Cloud, Self-hosted |
| Support | Docs |
| Built for | Solo, Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 2 integrations: LangGraph, CrewAI |
| Pricing | Free plan |
| Website | langchain-ai.github.io |
| Facts checked | 13 Oct 2026 |
LangMem integrations
LangMem lists 2 integrations on its own site.
- LangGraph
- CrewAI
Alternatives to LangMem
- Cloudflare Agent MemoryA cloud API for scoped, searchable memory across AI agent profiles and conversations.9.2
- Mem0A flexible memory layer with semantic, graph, and self-hosted deployment options.8.8
- MCP Memory ServiceA broad open-source memory layer for teams that can manage deployment and configuration.7.9
See all LangMem alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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