AI · alternatives · 2026

24 alternatives to Yet another memory system for LLMs

Built this for my LLM workflows - needed searchable, persistent memory that wouldn't blow up storage costs. I also wanted to use it locally for my research. It's a content-addressed storage system with block-level deduplication (saves 30-40% on typical codebases). I have integrated the CLI tool into most of my workflows in Zed, Claude Code, and Cursor, and I provide the prompt I'm currently using in the repo. The project is in C++ and the build system is rough around the edges but is tested on macOS and Ubuntu 24.04.

Yet Another Memory System for LLMs is a content-addressed storage system designed for developers using large language models in their workflows. It provides searchable, persistent memory while minimizing storage costs… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
A local-first memory store for LLM agents (SQLite)▲48
Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc. - CaviraOSS/LongMemory
Dec 2025 · github.com · its alternatives →
2
My LLM CLI tool can run tools now, from Python code or plugins▲529
LLM 0.26 is out with the biggest new feature since I started the project: support for tools. You can now use the LLM CLI tool—and Python library—to grant LLMs from …
2025 · simonwillison.net · its alternatives →
3
I used Claude Code to discover connections between 100 books▲524
I think LLMs are overused to summarise and underused to help us read deeper. I built a system for Claude Code to browse 100 non-fiction books and find interesting connections between them. I started out with a pipeline in stages, chaining together LLM calls to build up a context of the library. I was mainly getting back the insight that I was baking into the prompts, and the results weren't particularly surprising. On a whim, I gave CC access to my debug CLI tools and found that it wiped the floor with that approach. It gave actually interesting results and required very little orchestration…
Jan 2026 · trails.pieterma.es · its alternatives →
4
CodeYam CLI & Memory▲141
Comprehensive memory management for Claude Code
Mar 2026 · codeyam.com · its alternatives →
5
Find the best local LLM for your hardware, ranked by benchmarks▲283
Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. - Andyyyy64/whichllm
May 2026 · github.com · its alternatives →
6RG
Recall: Give Claude memory with Redis-backed persistent context▲171
Hey HN! I'm José, and I built Recall to solve a problem that was driving me crazy. The Problem: I use Claude for coding daily, but every conversation starts from scratch. I'd explain my architecture, coding standards, past decisions... then hit the context limit and lose everything. Next session? Start over. The Solution: Recall is an MCP (Model Context Protocol) server that gives Claude persistent memory using Redis + semantic search. Think of it as long-term memory that survives context limits and session restarts. How it works: - Claude stores important context as "memories" during…
2025 · npmjs.com · its alternatives →
7
Continual Learning with .md▲34
I have a proposal that addresses long-term memory problems for LLMs when new data arrives continuously (cheaply!). The program involves no code, but two Markdown files. For retrieval, there is a semantic filesystem that makes it easy for LLMs to search using shell commands. It is currently a scrappy v1, but it works better than anything I have tried. Curious for any feedback!
Apr 2026 · github.com · its alternatives →
8
Core – open source memory graph for LLMs – shareable, user owned▲112
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 →
9
Claude-Mem▲115
AI agent memory, everywhere. claude-mem is open-source memory for Claude Code; cmem links it to any MCP client — Cursor, Codex, more — via one private link.
Dec 2025 · cmem.ai · its alternatives →
10
LLM, a Rust Crate/CLI for CPU Inference of LLMs (LLaMA, GPT-NeoX, etc.)▲45
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
11
Trieve CLI – Terminal-based LLM agent loop with search tool for PDFs▲35
Hi HN, I built a CLI for uploading documents and querying them with an LLM agent that uses search tools rather than stuffing everything into the context window. I recorded a demo using the CrossFit 2025 rulebook that shows how this approach compares to traditional RAG and direct context injection[1]. The core insight is that LLMs running in loops with tool access are unreasonably effective at this kind of knowledge retrieval task[2]. Instead of hoping the right chunks make it into your context, the agent can iteratively search, refine queries, and reason about what it finds. The CLI handles…
2025 · github.com · its alternatives →
12
AI Memory Layer for ChatGPT and Claude.▲26
Shared persistent memory across all your LLMs.
2025 · teamlayer.xyz · its alternatives →
13
LLM-Term – Simple Rust-based CLI assist tool▲32
Current AI-assisted CLI tools are often part of larger systems and work better on Linux. I built llm-term to address these. It's a Rust-based tool that compiles into a single binary file. You only need to download the binary, add it to your PATH, and configure your OpenAI key to get started. While llm-term offers an option for gpt-4o, it works great with gpt-4o-mini. So it's not costly. I appreciate any feedback or suggestions.
2024 · github.com · its alternatives →
14
Mnexium AI▲83
Persistent, structured memory for AI Agents
Jan 2026 · mnexium.com · its alternatives →
15ZL
Zep – Long-Term Memory Store for LLM Apps▲7
Zep is a long-term memory store designed for conversational AI applications built using modern LLMs. It handles the storage, summarization, embedding, indexing, and enrichment of chat histories, and offers developers a simple, low-latency API to this data. Chat history storage is an infrastructure challenge all developers and enterprises face as they look to move from prototypes to deploying conversational AI applications that provide rich and intimate experiences to users. Key features include long-term memory persistence, auto-summarization, vector search, auto-token counting, and Python…
2023 · its alternatives →
16
Object database for LLMs that persists across chats (MCP server)▲9
I’d like to use LLMs for remembering all kinds of things: fitness, to-do lists, contacts, bug reports, research links, whatever. But there is no way to do that now. For example, if I find a great coding tutorial in chat, or tell it how much I ran yesterday, it forgets that when I close the chat. Even if I keep the chat history, I still need to scour through lots of messages to find the data I want. Ideally, Claude would remember all this, and I’d be able to find it later with ease. This is what my team built. It is a collaborative database you add to any LLM that supports MCP. (Claude Code,…
2025 · dry.ai · its alternatives →
17
I built simple and efficient local memory system for Claude Code▲6
I wanted to share a project I have been working on over the past week. It is a simple local memory system that saves your sessions into Markdown files, which can be viewed later. I developed this after using Claude Mem. I really enjoyed working with it, but it was consuming a lot of RAM, and each Claude session was becoming a major resource hog. I also tried other plugins and MCP solutions, but ran into similar issues, either slow performance or concerns about data being sent elsewhere. Because privacy was a big thing for me, I decided to build my own solution that keeps all data local.
Feb 2026 · github.com · its alternatives →
18
Use local LLMs to organize your files▲6
Hi everyone, Just wanted to share a use case where local LLMs are genuinely helpful for daily workflows: file organization. I've been working on a C++ desktop app called AI File Sorter – it uses local LLMs via `llama.cpp` to help organize messy folders like `Downloads` or `Desktop`. Not sort files into folders solely based on extension or filename patterns, but based on what each file actually is supposed to do or does. Basically: what would normally take me a great deal of time for dragging and sorting can now be done in a few. It's cross-platform (Windows/macOS/Linux), and fully…
2025 · github.com · its alternatives →
19
LLM Memory Storage that scales, easily integrates, and is smart▲6
I built a super easy to integrate memory storage and retrieval system for NodeJS projects because I saw a need for information to be shared and persisted across LLM chat sessions (and many other LLM feature interactions). I tried to keep the barrier to use as low as possible so I included built-in support for major LLMs (GPT, Gemini, and Claude) as well as major vector store providers (Weaviate and Pinecone). The memory store works by ingesting and automatically extracting “memories” (summarized single bits of information) from LLM interactions and vectorizing those. When you want to provide…
Mar 2026 · github.com · its alternatives →
20CM
CodeYam Memory – comprehensive memory management for Claude Code▲17
We built CodeYam Memory because Claude Code kept making the same mistakes on our codebase. Our claude.md files quickly got stale and maintaining by hand or with Claude wasn’t sufficient. While digging into this we found that Claude has a native rules system that allowed us to target specific parts of our repo with path matching. This was ideal for our use case but trying to manage these rules by hand was already not working and would be even harder with more granular, targeted rules. CodeYam Memory uses a background agent to review your coding session transcripts, identifies confusion…
Mar 2026 · its alternatives →
21
I built a CLI that turns your codebase into clean LLM input▲10
A simple CLI that transforms your code into clean, structured text for feeding into LLMs. - NoahCristino/llmcat
Apr 2026 · github.com · its alternatives →
22
A CLI that makes LLMs convenient to use for developers▲26
Command-line interface for the Arcane Engine. Contribute to arc-eng/cli development by creating an account on GitHub.
2024 · github.com · its alternatives →
23
xMem▲8
Memory Orchestrator for LLMs
2024 · xmem.xyz · its alternatives →
24WM
Which Mac runs which LLM, and how fast▲10
Pick a Mac and a model, get the memory it needs and the tokens/sec to expect. Covers M1 to M6, every unified memory size, Q4 to FP16. Formula fitted and validated on our own measurements on two machines.
4d ago · macyou.co · 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 →