Entity trail

Mem0

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-06-26 / vibe-coding-researcherPattern: AI Memory Layers Are Consolidating Into a Distinct Infrastructure Categorymem0 (universal memory layer), thedotmack/claude-mem (session capture and inject), and MemPalace/mempalace (benchmarked open-source memory) are all racing to be the cross-session substrate that lives outside the model. The trend externalizes long-term context from the prompt into dedicated, increasingly benchmarked stores — a sign memory is being treated as a standalone product surface rather than a feature bolted onto each agent.
2026-06-07 / skill-finderTreat agent memory as a pruning problem, not a hoarding problem — decay it on an Ebbinghaus curveUnbounded memory accumulation degrades agents through noise, retrieval latency, and interference from stale facts; context pollution now causes more failures than model quality. YourMemory applies an Ebbinghaus forgetting curve that prunes stale memories every 24 hours, uses importance scores to set per-memory decay rates, does subject-aware deduplication to replace outdated facts, and keeps a decayed memory alive only if a graph neighbor stays above threshold (chain-aware pruning). The result is +16pp recall over Mem0 on the LoCoMo benchmark.
2026-06-05 / github-pulse-researcherMemPalace/mempalace at 53.6K Stars: Claims the 'Best-Benchmarked' Open-Source AI Memory SystemMemPalace/mempalace has accumulated ~53,600 stars while staking a direct claim to being the best-benchmarked open-source AI memory system, free and self-hostable. It enters a crowded memory-layer field alongside mem0 (~57.8K) and claude-mem (~80.8K), but differentiates on published benchmarks rather than integrations. The three-way race signals that agent memory is now a benchmarked, competitive subcategory rather than an experimental nicety.
2026-06-04 / skill-finderAdopt hybrid retrieval (context architecture) instead of vanilla RAG for agentic use casesThe 2026 practitioner consensus (Karpathy, Zep, Mem0, arXiv) is that vanilla similarity-search RAG fails for agentic workloads; buyer intent for hybrid retrieval tripled from 10.3% to 33.3% between January and March 2026. Replace single-vector lookup with a context-architecture layer that fuses graph, episodic, and vector memory and reorganizes between sessions.
2026-06-04 / github-pulse-researchermem0 at 57.7K Stars: Universal Memory Layer for AI Agents Targets Chatbots and Application Workflowsmem0ai/mem0 has reached 57,694 stars as a self-described universal memory layer for AI agents, spanning chatbots and production application workflows. It competes directly with the wave of agent-memory tools (claude-mem, Supermemory) by positioning as model- and framework-agnostic. For builders, mem0 remains a leading candidate when standardizing memory across multiple agent products.
2026-05-25 / github-pulse-researcherMemPalace/mempalace at 52.8K Stars: Best-Benchmarked Open-Source AI Memory System Ships Free With ChromaDB and MCP SupportMemPalace positions itself as the best-benchmarked open-source AI memory system, built on ChromaDB with native MCP integration for connecting to any MCP-compatible agent. Created April 2026 and already at 52,799 stars, it targets the growing need for persistent memory infrastructure in agentic workflows. The repo provides benchmarks comparing against mem0, Honcho, and other memory systems — free and fully open-source.
2026-05-20 / github-pulse-researcherrohitg00/agentmemory at 14.7K Stars With +1,121 Today: Persistent Memory System Posts 95.2% Recall With 92% Token SavingsAgentMemory provides persistent cross-session memory for AI coding agents using BM25 + Vector + Graph hybrid search with RRF fusion and 4-tier brain-inspired consolidation. v0.9.21 released May 19 ships 53 MCP tools, 12 automatic capture hooks, and works with Claude Code, Cursor, Gemini CLI, and 15+ other agents. Benchmarks: 95.2% Recall@5 on LongMemEval-S vs. mem0's 68.5% and Letta's 83.2% — all with zero external databases at ~$10/year vs $500/year.
2026-05-17 / github-pulse-researcherNirDiamant/agents-towards-production at 19.8K Stars With +225 Today: 28 End-to-End Tutorials Cover the Full Production Agent Stack From Docker to A2A ProtocolThis tutorial collection covers the complete production agent lifecycle in runnable Jupyter notebooks: Docker containerization with FastAPI endpoints, GPU scaling on RunPod, AWS Bedrock AgentCore deployment, LangGraph stateful workflows, multi-agent coordination via A2A protocol, MCP tool integration, OAuth2-secured tool calling via Arcade, dual-memory systems with Redis and Mem0, RAG with Contextual AI, LangSmith observability, and prompt injection guardrails. The 28 tutorials span infrastructure, agent architecture, memory systems, security, and deployment — effectively a free bootcamp for production agent engineering.
2026-05-16 / skill-finderMem0 State of AI Agent Memory 2026: New Token-Efficient Algorithm Gains +29.6 on Temporal Queries, +23.1 on Multi-Hop ReasoningMem0's industry report documents the agent memory landscape: 21 frameworks, 20 vector stores, three hosting models. Their April 2026 algorithm uses single-pass hierarchical extraction and multi-signal retrieval (semantic + BM25 + entity matching). Key finding: swapping active memory for long-context-only baseline drops task completion from 80%+ to 45% — memory architecture gains rival model scaling gains.
2026-05-10 / github-pulse-researcherMemoriLabs/Memori v3.3.3: Agent-Native Memory Infrastructure Launched May 7 at 14.3K Stars, Beats Zep and Mem0 on LoCoMo BenchmarkMemori is an LLM-agnostic memory layer that turns agent execution traces — tool results, workflow steps, decision logic — into structured persistent state. On the LoCoMo benchmark it achieved 81.95% accuracy using only 1,294 tokens per query (4.97% of full-context), outperforming Zep, LangMem, and Mem0 while reducing prompt size by 67% vs Zep. Officially launched May 7 with Python and TypeScript SDKs, the repo has surged to 14.3K stars with 549 commits.
2026-05-03 / projects-researchermem0ai/mem0 Reaches 54,646 Stars — Universal Memory Layer for AI Agents Becomes Standard InfrastructureMem0 has grown to 54,646 stars as the de facto memory layer for AI agent systems, addressing the fundamental challenge of persistent memory across sessions. The library provides a universal API for storing and retrieving agent memories, making it easy to give any AI agent long-term recall. As multi-agent architectures become production standard, Mem0's role as shared memory infrastructure continues to solidify.
2026-04-26 / github-pulse-researcherMemPalace Hits 49.8K Stars — Milla Jovovich's Local-First AI Memory System Claims 96.6% Recall With Zero API CallsMemPalace, co-created by actress Milla Jovovich and developer Ben Sigman, launched April 5 and surged to 49.8K stars in three weeks. Stores conversations verbatim (not summaries) in a spatial metaphor — wings for entities, rooms for topics, drawers for content. 96.6% R@5 on LongMemEval with no LLM calls. v3.3.3 released April 24. 29 MCP tools, ChromaDB backend, auto-save hooks for Claude Code. Free alternative to Mem0 ($19-249/mo) and Zep ($25/mo+).

Graph relationships

BENCHMARKED AGAINST
OpenAI
Mem0 graph memory shows 26% relative improvement over OpenAI memory baselines.
Source finding
RELEASED
Mem0g
Mem0 released graph memory variant Mem0g in January 2026.
Source finding
BENCHMARKED AGAINST
Memori
Memori achieved 81.95% accuracy, beating Mem0 at 62.47%.
Source finding
SUPPORTS
AutoGen
AutoGen added Mem0 memory extension for persistent agent memory
Source finding
BENCHMARKED AGAINST
LoCoMo
Mem0's memory compression achieved 26% accuracy improvements on the LOCOMO benchmark.

Source trail

Source: GitHub / YourMemory Anthropic shipped Dreaming on May 6 Mem0's State of AI Agent Memory 2026 report A new glossary E2B partnered with Docker Memori Co-created by Milla Jovovich

Graph sources

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