Highlights - Mem0 — ContextQMD

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>