AI · alternatives · 2026
24 alternatives to MemoryOS
Hybrid AI Memory: Vector RAG meets Knowledge Graphs
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Memorize, organize & amplify your thoughts
2024 · second.me · its alternatives →
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Hey HN! I built a proof-of-concept for AI memory using Git instead of vector databases. The insight: Git already solved versioned document management. Why are we building complex vector stores when we could just use markdown files with Git's built-in diff/blame/history? How it works: Memories stored as markdown files in a Git repo Each conversation = one commit git diff shows how understanding evolves over time BM25 for search (no embeddings needed) LLMs generate search queries from conversation context Example: Ask "how has my project evolved?" and it uses git diff to show actual…
2025 · github.com · its alternatives →
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Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
2024 · github.com · its alternatives →
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Memori▲168Persistent memory from agent trace, not just conversation
May 2026 · memorilabs.ai · its alternatives →
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DeltaMemory▲104Most AI agents forget everything between sessions. We built DeltaMemory to fix that. It's a cognitive memory layer that gives agents persistent recall, automatic fact extraction, and temporal reasoning — via a single SDK call. Key numbers: - 89% accuracy on LoCoMo long-term conversation benchmark - 50ms p50 retrieval latency - 97% cost reduction vs raw token re-processing Open source SDKs, works with any LLM stack. Currently in early access. Happy to answer questions about the architecture, benchmark methodology, or how we handle knowledge graphs.
Feb 2026 · deltamemory.com · its alternatives →
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I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
2024 · embedding.io · its alternatives →
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Local-first AI memory layer for any LLM. Persistent knowledge graph, entity extraction, semantic retrieval. Works with Ollama, OpenAI, Anthropic, or any OpenAI-compatible backend. - zaydmulani09/mnemo
Jun 2026 · github.com · its alternatives →
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Query Memory▲100One API for all documents your AI agents need
Mar 2026 · querymemory.com · its alternatives →
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An OKF-backed Model Context Protocol (MCP) server delivering persistent long-term memory and SQLite FTS5 search for AI agents. - fellowgeek/mcp-memory
Aug 2026 · github.com · its alternatives →
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Most RAG setups fail because they treat memory like a static filing cabinet. When every transient bug fix or abandoned rule is stored forever, the context window eventually chokes on noise, spiking token costs and degrading the agent's reasoning. This implementation experiments with a biological approach by using the Ebbinghaus forgetting curve to manage context as a living substrate. Memories are assigned a "strength" score where each recall reinforces the data and flattens its decay curve (spaced repetition), while unused data eventually hits a threshold and is pruned. To solve the…
Apr 2026 · github.com · its alternatives →
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Papr▲113Predictive memory and context intelligence API for AI Agents
Dec 2025 · papr.ai · its alternatives →
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YourMemory▲93This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…
Apr 2026 · yourmemoryai.vercel.app · its alternatives →
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Biologically-inspired memory for AI agents. Decay, retrieval strengthening, consolidation. Zero dependencies. - kitfunso/hippo-memory
Apr 2026 · github.com · its alternatives →
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I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…
2025 · github.com · its alternatives →
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AI agent memory with knowledge graph and 78ms retrieval
May 2026 · github.com · its alternatives →
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memories.sh▲50One layer for memories, skills, and rules across any agent
Feb 2026 · memories.sh · its alternatives →
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Vector databases store memories. They don't manage them. After 10k memories, recall quality degrades because there's no consolidation, no forgetting, no conflict resolution. Your AI agent just gets noisier. YantrikDB is a cognitive memory engine — embed it, run it as a server, or connect via MCP. It thinks about what it stores: consolidation collapses duplicate memories, contradiction detection flags incompatible facts, temporal decay with configurable half-life lets unimportant memories fade like human memory does. Single Rust binary. HTTP + binary wire protocol. 2-voter + 1-witness HA…
Apr 2026 · github.com · its alternatives →
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MemoryOS▲3Offline, AI-powered local file search for Windows
Jul 2026 · github.com · its alternatives →
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Tired of AI coding tools that forget everything between sessions? Every time I open a new chat with Claude or fire up Copilot, I'm back to square one explaining my codebase structure. So I built something to fix this. It's called In Memoria. Its an MCP server that gives AI tools persistent memory. Instead of starting fresh every conversation, the AI remembers your coding patterns, architectural decisions, and all the context you've built up. The setup is dead simple: `npx in-memoria server` then connect your AI tool. No accounts, no data leaves your machine. Under the hood it's TypeScript +…
2025 · github.com · its alternatives →
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An agent that remembers across sessions can keep its memory as curated markdown files, as an auto-mined structured store, or as trained experience.
Aug 2026 · pinglin.tw · its alternatives →
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Semantic search alone is not enough to capture all connected facts, they will capture the semantically most identical memory only. Tested on HotpotQA public dataset: Vector + BM25 + entity graph: BothFound@5 71.5% Vector + BM25 only: BothFound@5 59.5% Entity graph is the game changer to extract connected facts. More Benchmark result: LongMemEval-S: 84.8% recallAll@5 LoCoMo-10: 59% vs zep cloud 28% What is your approach for connected facts retrieval ?
Jul 2026 · yourmemoryai.xyz · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →