SDK Memory Expiration: Expiring Memories Across Python and TypeScriptThe 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()andAsyncMemoryClient.update()now acceptexpiration_date, includingNoneto clear an existing expiration. - TypeScript client updates:
AddMemoryOptions,update(), andMemorynow supportexpirationDate;search()andgetAll()can include expired memories withshowExpired. - New TypeScript LLM providers:
MiniMaxLLMandLiteLLMare now available for OpenAI-compatible MiniMax and LiteLLM proxy deployments. - PGVector deployment flexibility: TypeScript PGVector config now supports
connectionStringandssl, so apps can use a managed Postgres URI instead of separate connection fields.
Mem0 Plugin: Shared Memory for Claude Code, Cursor, Codex, and AntigravityThe shared Mem0 editor plugin is current through v0.2.11:
- Automatic context injection: File reads, bash errors, session resume prompts, and startup timelines can retrieve relevant memories automatically.
- Project and global scopes: Project-scoped memories remain the default, while
global_searchsupports team-wide recall across users and app scopes. - Coding categories: A 17-category coding taxonomy installs in the background and is cached per Mem0 account.
- Reliable capture: Auto-capture, compaction summaries, session summaries, and metadata defaults keep memories scoped and readable.
- Editor correctness: Telemetry now reports Claude Code, Cursor, Codex, and Antigravity separately with each editor’s real plugin version.
Antigravity Plugin: Mem0 for Google AntigravityAntigravity support in the shared Mem0 editor plugin family is current through v0.1.3:
- Self-contained plugin: Includes its own plugin manifest, MCP config, hooks, shared scripts, and skills.
- AGENTS.md convention: Uses Antigravity’s
contextFileName: "AGENTS.md"convention. - Lifecycle hooks: Wires session start, prompt recall, file-read context, memory-tool metadata enforcement, bash-error lookup, post-tool tracking, and stop summaries.
- Shared memory layer: Reuses the Mem0 Platform MCP tools and the shared 16-skill command bundle.
- Better automatic recall: v0.1.3 adds reranked injected context and clean
files_touchedmetadata in session summaries. - Telemetry correctness: v0.1.2 reports Antigravity as
antigravitywith the plugin’s own version.
OpenCode Plugin: Native SDK Memory Tools for OpenCode
@mem0/opencode-plugin adds memory to OpenCode and is current through v0.2.0:- Native SDK tools: Memory tools register through
@opencode-ai/pluginand call themem0aiSDK directly, so the plugin no longer depends onmcp.mem0.ai. - Memory scopes: Operations support
project,session, andglobalscope, with/mem0-scopeto change the default. - Automatic context: File-context injection, structured compaction summaries, and a recent-activity timeline surface relevant memories without manual recall.
- Auto-dream consolidation: Gated consolidation merges duplicates, drops stale or sensitive entries, and rewrites vague memories.
- Skills load in place: The
confighook adds bundled skills toskills.pathsinstead of copying them into user config directories. - Safety controls: Blocks
MEMORY.mdwrites and redacts secrets before storing memories.
Pi Agent Plugin: Persistent Memory for Pi Agent
@mem0/pi-agent-plugin adds semantic memory to Pi Agent and has been updated through v0.1.2:- Agent memory tool: Registers
mem0_memoryfor scoped search, add, get, delete, and delete-all operations. - Slash commands: Adds
/mem0-remember,/mem0-search,/mem0-forget,/mem0-tour,/mem0-dream,/mem0-pin,/mem0-scope, and/mem0-status. - Auto-capture: Stores user and assistant memories after agent turns.
- Dream consolidation: Merges duplicates, resolves contradictions, and prunes stale memories behind session, time, and memory-count gates.
- Project scoping: Uses git-root detection for stable
app_idvalues across monorepos. - Relevant command results: v0.1.2 adds visible command feedback and thresholded, reranked search for search, forget, and pin commands.
OpenClaw Plugin: Current Memory Backend for OpenClaw
@mem0/openclaw-mem0 is current through v1.0.13, with the original production-ready memory backend plus newer setup, security, and runtime work:- Skills-based memory architecture: Triage, recall, and dream skills handle extraction, recall, consolidation, and tool guidance.
- Chat and CLI setup: Supports chat-based platform setup,
openclaw mem0 init, direct API keys, email OTP, autonomous agent setup, and OSS onboarding. - Platform and OSS modes: Works with Mem0 Platform or self-hosted OSS providers including OpenAI, Anthropic, Ollama, Qdrant, and PGVector.
- Agent-friendly CLI: All 16 CLI commands support
--jsonfor machine-driven setup and diagnostics. - Runtime integration: Exposes OpenClaw memory capability APIs for search manager and backend config status.
- Security and compliance: Added path containment checks, sensitive config metadata, dependency overrides, telemetry hashing, and metadata-only registration safety.
Vercel AI SDK Provider: Memory-Augmented Generation for AI SDK v6The Vercel AI SDK provider moved to the v6 provider contract and Mem0 v3 APIs:
- AI SDK v6 support: Migrated to
LanguageModelV3/ProviderV3, including v3 stream lifecycle events and content arrays. - Mem0 v3 API support: Memory writes and searches now use
/v3/memories/add/and/v3/memories/search/. - Mem0 sources in responses:
generateTextandstreamTextresponses include memories as sources withproviderMetadata.mem0.memories. - Safer prompt handling: Prompts are cloned before memory injection, avoiding caller-side mutation.
- Async storage fix:
addMemoriesis awaited so generated memories are not silently dropped. - Raw memory utilities: Exports
searchMemories,retrieveMemories,getMemories, andaddMemoriesfor apps that need direct memory control. - Deployment controls: Per-request
mem0ApiKeyandhostsupport Mem0 Platform, custom API keys, and self-hosted API endpoints.
Temporal Reasoning: Time-Aware Retrieval for Platform v3Mem0 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, andas of March 2025now resolve against memory timestamps automatically. - Default v3 behavior: No per-request toggle is needed for v3 writes or searches.
- Deterministic testing: Pass
reference_dateto anchor relative phrases in tests, backfills, and demos. - Stable API shape: Temporal reasoning changes ranking, not the client response contract.
Memory Decay: Recently-Used Memories Surface HigherPer-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.
New Memory Algorithm: State-of-the-Art Accuracy at ~3-4x Lower CostGround-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
search() defaults changed, deprecated params removed. See migration guide.Mem0 Skill Graph: In-Context Documentation for AI AgentsAI 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 npmA full-featured command-line interface for Mem0, available in both Python and Node.js:
- Install:
pip install mem0-cliornpm install -g @mem0/cli - Full command suite:
add,search,list,get,update,delete,import,config,init,status,entity,event. - Interactive setup:
mem0 initsupports email verification and direct API key entry. - Runtime coverage: Works with Mem0 Platform and self-hosted OSS modes.
- Automation support: Use
--jsonfor CI/CD pipelines and agent workflows. - Dual implementation: Same commands and behavior across Python and Node.js.
Apache AGE, Turbopuffer, MiniMax, and pgvector for Node.jsMajor 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.
- 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_effortparameter for OpenAI o1/o3-style models.