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Highlights

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<Update label="2026-05-13" description="Temporal Reasoning for Mem0 Platform v3">

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.

  • Time-aware search intent — Queries like last week, upcoming, right now, and as of March 2025 return contextually appropriate results automatically
  • Enabled by default — No per-request toggle required for v3 writes or searches
  • Anchored relative queries — reference_date anchors relative search phrases for tests, backfills, and reproducible demos
  • Normal response shape — Temporal reasoning affects ranking while preserving existing client response patterns

See Temporal Reasoning for usage details.

</Update> <Update label="2026-05-08" description="Memory Decay">

Memory Decay — Recently-Used Memories Surface Higher, Automatically

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 zeros them out — 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.
</Update> <Update label="2026-04-14" description="Mem0 SDK v2.0.0 / v3.0.0">

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) — multi-turn conversation recall
  • LongMemEval: 67.8 → 93.4 (+26) — long-term memory across sessions
  • BEAM (1M tokens): 64.1 — production-scale memory evaluation
  • Agent memories are first-class — Previous algorithm: 46% on assistant recall. New: 100%
  • Temporal reasoning works — "Where did I live before SF?" Previous: 51%. New: 93%
  • ~3-4x fewer tokens — Under 7K tokens per retrieval vs 25K+ for full-context approaches
  • ADD-only extraction — Memories accumulate; nothing is overwritten or deleted
  • Hybrid retrieval — Semantic + BM25 keyword + entity boost, scored in parallel
  • Entity linking — Entities extracted, embedded, and linked across memories

Breaking changes: Graph memory removed from OSS, search() defaults changed, deprecated params removed. See migration guide.

</Update> <Update label="2026-04-06" description="Mem0 Skill Graph">

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 — no doc searching required. Three interconnected skills launched:

  • mem0 Core Skill — Complete 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
</Update> <Update label="2026-04-06" description="Mem0 CLI v0.2.2">

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 with email verification or direct API key entry
  • Works everywhere — Platform (Mem0 Cloud) and self-hosted OSS modes
  • Scriptable — --json flag for CI/CD pipelines and automation
  • Dual SDK — Same commands, same experience across Python and Node.js
</Update> <Update label="2026-04-06" description="OpenClaw v1.0.4">

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 4 legacy tools, matching the platform API
  • Security hardened — Path traversal protection, pinned dependencies, 329 tests across 10 files
</Update> <Update label="2026-04-02" description="Mem0 Plugin for AI Editors">

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, 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
</Update> <Update label="2026-03-21" description="New Providers">

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)
  • 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
</Update> <Update label="2026-03-14" description="Mem0 Platform Skill">

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 for any compatible AI coding agent.

</Update>