---
title: "Highlights"
description: "Major product launches, headline features, and milestones for Mem0."
mode: "wide"
---
**SDK Memory Expiration: Expiring Memories Across Python and TypeScript**
The latest SDK releases add first-class expiration controls to memory writes, updates, and reads, plus new TypeScript provider coverage for production deployments.
- **Python client updates:** `MemoryClient.update()` and `AsyncMemoryClient.update()` now accept `expiration_date`, including `None` to clear an existing expiration.
- **TypeScript client updates:** `AddMemoryOptions`, `update()`, and `Memory` now support `expirationDate`; `search()` and `getAll()` can include expired memories with `showExpired`.
- **New TypeScript LLM providers:** `MiniMaxLLM` and `LiteLLM` are now available for OpenAI-compatible MiniMax and LiteLLM proxy deployments.
- **PGVector deployment flexibility:** TypeScript PGVector config now supports `connectionString` and `ssl`, so apps can use a managed Postgres URI instead of separate connection fields.
See [SDK & Tools](/changelog/sdk) for version details and PR links.
**Temporal Reasoning: Time-Aware Retrieval for Platform v3**
Mem0 Platform v3 can now interpret time-aware memories and queries so assistants retrieve the right information for questions about the past, upcoming plans, and current state.
- **Search intent parsing:** Queries like `last week`, `upcoming`, `right now`, and `as of March 2025` now resolve against memory timestamps automatically.
- **Default v3 behavior:** No per-request toggle is needed for v3 writes or searches.
- **Deterministic testing:** Pass `reference_date` to anchor relative phrases in tests, backfills, and demos.
- **Stable API shape:** Temporal reasoning changes ranking, not the client response contract.
See [Temporal Reasoning](/platform/features/temporal-reasoning) for usage details.
**Memory Decay: Recently-Used Memories Surface Higher**
Per-project search-time ranking bias that boosts recently-touched memories and gently dampens stale ones. Off by default; opt in per project via the `decay` field on the project endpoint, or via `client.project.update(decay=True)` in the SDKs (Python `v2.0.2` / TypeScript `v3.0.3`).
- **Soft bias, never a filter.** The scaling factor stays in `0.3×–1.5×`. Decay can reorder candidates but never removes them; anything that surfaced before decay can still surface after.
- **Reinforcement loop.** Every memory returned in a search has its access history updated, so frequently-used facts naturally float to the top over time.
- **Public score still clamped to `[0, 1]`.** Existing API contract preserved; no client-side changes needed.
- **v3 search only**, fully reversible. See [Memory Decay docs](/platform/features/memory-decay).
**New Memory Algorithm: State-of-the-Art Accuracy at ~3-4x Lower Cost**
Ground-up rewrite of the memory pipeline with 20+ point benchmark improvements:
- **LoCoMo:** 71.4 → **91.6** (+20) for multi-turn conversation recall.
- **LongMemEval:** 67.8 → **93.4** (+26) for long-term memory across sessions.
- **BEAM (1M tokens):** **64.1** on production-scale memory evaluation.
- **Agent memories:** Assistant recall moves from 46% to **100%**.
- **Temporal reasoning:** "Where did I live before SF?" improves from 51% to **93%**.
- **Lower token use:** Retrieval stays under 7K tokens versus 25K+ for full-context approaches.
- **ADD-only extraction:** Memories accumulate; nothing is overwritten or deleted.
- **Hybrid retrieval:** Semantic search, BM25 keyword search, and entity boost are scored in parallel.
- **Graph memory (built-in)**: entities extracted, embedded, and linked across memories, with no external graph store required
Breaking changes: external graph stores removed from OSS (replaced by built-in graph memory), `search()` defaults changed, deprecated params removed. See [migration guide](/migration/oss-v2-to-v3).
**Mem0 Skill Graph: In-Context Documentation for AI Agents**
AI coding agents in Claude Code, Cursor, and Codex can now access Mem0 knowledge directly in their workflow without leaving the editor. Three interconnected skills launched:
- **mem0 Core Skill:** Python and TypeScript SDK reference, REST API patterns, and integration guides for LangChain, CrewAI, Autogen, and more.
- **mem0-cli Skill:** Terminal command reference, configuration walkthroughs, and CI/CD recipes.
- **mem0-vercel-ai-sdk Skill:** Vercel AI SDK provider API, memory-augmented generation patterns, and multi-provider setup.
**Official Mem0 CLI: Now on PyPI and npm**
A full-featured command-line interface for Mem0, available in both Python and Node.js:
- **Install:** `pip install mem0-cli` or `npm install -g @mem0/cli`
- **Full command suite:** `add`, `search`, `list`, `get`, `update`, `delete`, `import`, `config`, `init`, `status`, `entity`, `event`.
- **Interactive setup:** `mem0 init` supports email verification and direct API key entry.
- **Runtime coverage:** Works with Mem0 Platform and self-hosted OSS modes.
- **Automation support:** Use `--json` for CI/CD pipelines and agent workflows.
- **Dual implementation:** Same commands and behavior across Python and Node.js.
**OpenClaw Plugin: Production-Ready**
The OpenClaw Mem0 plugin went from initial release to production-ready in one week (v1.0.0 → v1.0.4):
- **Skills-based memory architecture:** New extraction pipeline with skill-loader, batched extraction, and domain-aware memory triage.
- **Dream gate:** Automatic memory consolidation during idle periods for higher-quality long-term recall.
- **Interactive CLI:** `openclaw mem0 init`, `status`, `config`, `import`, and `event` commands.
- **Unified tool naming:** `memory_add` and `memory_delete` replace four legacy tools and match the platform API.
- **Security hardened:** Path traversal protection, pinned dependencies, and 329 tests across 10 files.
**Mem0 Plugin for Claude Code, Cursor, and Codex**
Launched a unified Mem0 plugin across three major AI development environments: Claude Code and Cursor first (March 25), then Codex (April 2).
- **9 MCP memory tools:** Add, search, get, update, delete, bulk delete, and entity management via `mcp.mem0.ai`.
- **Lifecycle hooks:** Automatic memory capture at session start, context compaction, task completion, and session end.
- **Cloud MCP server:** Managed endpoint replaces local MCP and Smithery setup.
- **Streamable HTTP transport:** New MCP transport protocol for real-time streaming.
- **Codex-specific skill:** Dedicated skill in `mem0-plugin/skills/mem0-codex` for Codex workflows.
**Apache AGE, Turbopuffer, MiniMax, and pgvector for Node.js**
Major expansion of the provider ecosystem:
- **Apache AGE:** New graph store support, bringing the total to 4 graph store backends (Neo4j, Memgraph, Kuzu, Apache AGE). **Note:** All external graph store backends (Neo4j, Memgraph, Kuzu, Apache AGE) were subsequently removed in v2.0.0 (2026-04-14). Graph memory is now built-in entity linking with no external graph store required; see the [v2.0.0 entry above](#mem0-sdk-v2-0-0-v3-0-0).
- **Turbopuffer:** New vector database provider for Python SDK.
- **MiniMax:** New LLM provider with dedicated AWS Bedrock support.
- **pgvector for Node.js:** PostgreSQL vector support added to the TypeScript OSS SDK.
- **Reasoning models:** `reasoning_effort` parameter for OpenAI o1/o3-style models.
**Mem0 Platform Skill on skills.sh**
First skill launch: a dedicated Mem0 skill providing platform API reference, quickstart patterns, and integration examples directly inside agent sessions. Available on [skills.sh](https://skills.sh) for any compatible AI coding agent.