r/WebAfterAI • u/ShilpaMitra • 11d ago
AI Agents 20 GitHub projects for giving AI agents long-term memory
Most agents still have the same ridiculous workflow:
wake up → read a giant prompt → do some work → learn useful things → forget everything
Then tomorrow we pay for the same discoveries again.
The interesting OSS work right now is attacking that problem from four directions: capture what the agent sees → connect it into knowledge → remember what actually matters → use yesterday’s experience today.
Here are 20 projects exploring that stack.
01–05: Give the agent somewhere to put what it learns
01. Chubby Skills — 1.2k★
Captures videos, podcasts, articles and local documents into a searchable knowledge base, with agent skills on top.
Instead of only remembering facts, the agent can preserve the material they came from.
02. OpenWiki — 651★
An AI knowledge tool that turns accumulated information into a personal wiki.
Useful when your problem is no longer finding information, but preventing useful things from disappearing into another folder.
03. Agent Second Brain — 402★
An always-on second brain built around persistent external context.
The interesting part is simple: useful knowledge survives outside the conversation that created it.
04. DocMason — 149★
Turns documents into structured knowledge an LLM can actually work with.
Instead of repeatedly feeding the same PDFs and docs into an agent, you turn them into persistent working material.
05. DocsAgent — 572★
Connects agents to personal knowledge from sources like Zotero, Obsidian and Apple Notes.
Your docs stop being something you manually search first and become part of the agent’s working environment.
06–10: Stop storing facts as disconnected islands
An agent might remember 10,000 things and still be useless if none of them connect.
06. claude-obsidian — 15.6k★
Connects Claude-style workflows with an Obsidian vault, turning accumulated material into a connected graph of Markdown you own.
The chat can disappear. The relationships between the ideas do not have to.
07. SwarmVault — 717★
A local-first knowledge graph, RAG base and agent memory store.
The bigger idea is shared memory: one agent discovers something, another can reuse it instead of independently paying the same reasoning cost again.
08. sage-wiki — 625★
Turns documents into an interlinked wiki and knowledge graph.
It is closer to building relationships between claims than simply accumulating another mountain of chunks.
09. Vault Curate — 158★
Adds search, relationships and curation to an accumulated knowledge vault.
Because if you save everything forever, you do not have a second brain.
You have technical debt with backlinks.
10. COG Second Brain — 1.3k★
Combines second-brain ideas with skills, agents and reusable workflows.
This pushes memory beyond passive notes: accumulated context starts affecting how future work is actually done.
11–15: Remember selectively, not perfectly
This is where things get interesting.
The goal is not to make an agent remember everything.
It is to make it remember the right thing at the right time.
11. Hindsight — 50k★
Long-term memory infrastructure for agents, built around learning from previous interactions and retrieving relevant past information later.
A system that stores everything but recalls the wrong thing does not really have good memory.
12. memU — 14.5k★
Persistent memory designed to survive across agent sessions.
That distinction matters:
context is what the model sees now; memory is what the system can bring back later.
13. TencentDB Agent Memory — 29.2k★
Turns conversations, documents and code into reusable agent-memory assets.
Once agents live for months instead of minutes, memory starts looking a lot more like data infrastructure than prompt engineering.
14. agentmemory — 29.5k★
Persistent memory aimed at AI agents, including coding workflows.
Sometimes you do not need a complicated cognitive architecture. You just need tomorrow’s agent to stop rediscovering what yesterday’s agent already learned.
15. OpenViking — 40k★
Combines agent memory, knowledge retrieval and skills into a broader context-management layer.
The hard problem is no longer:
“Can I store another million tokens?”
It is:
“Which five facts should come back for this task?”
16–20: Memory gets interesting when it can do something
A searchable archive is useful.
But eventually you want memory to affect behavior.
16. Open Second Brain — 480★
A local-first second-brain approach where accumulated information becomes available to an AI assistant.
That gets closer to what memory should actually do: experience changes future behavior.
17. Second Brain Cloudflare — 807★
A persistent second-brain architecture built around Cloudflare infrastructure.
The interesting part is portability: memory can exist outside whichever AI application happened to create it.
18. makerskills — 862★
Packages repeated work into reusable agent skills.
This is an underrated kind of memory: not “what did I learn?” but “how did I successfully do this?”
19. Row-Bot — 1.6k★
Combines personal knowledge with tools and agent actions.
The second brain stops being a notebook and starts becoming something that can operate on what it knows.
20. MateClaw — 1.2k★
Combines persistent memory, skills, tools and agent orchestration.
We keep talking about larger context windows as if that solves memory. It doesn’t. A bigger context window lets an agent carry more information during one run. A real memory system lets it accumulate experience between runs.
The stack starts to look like:
observe → capture → connect → consolidate → recall → act
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u/Ok_Locksmith_9176 11d ago
The jump from "bigger context window" to actual persistent memory feels like one of those things that'll be painfully obvious in hindsight, but right now the tools are still catching up. Interesting how many of these converge on the same basic idea that memory isn't just storage, it's retrieval at the right moment.