
Remem — Persistent Memory API for AI Agents
Persistent memory API for AI agents. Hybrid scoring (semantic + recency + importance) that works with LangGraph, AutoGen, and CrewAI. Free to start.
@sunvic567 · X
The full gallery
Tech stack
61 projects

Persistent memory API for AI agents. Hybrid scoring (semantic + recency + importance) that works with LangGraph, AutoGen, and CrewAI. Free to start.
@sunvic567 · X

Hosted JSON database for storing agent memory with REST and MCP connectivity
@StuSim · X
hey Adam, I run , lightweight agent memory

Task manager with Now, Next, and Someday buckets that sync between iOS and web.
u/dahooddawg · Reddit
I built a task manager that replaces priority levels with a hard cap on what "now" means Hey r/SideProject -- I built this for myself because every task manager I tried had the same problem: everything felt high priority. The core idea: instead of High/Med/Low (which fails because everything feels high), you get three buckets -- Now, Next, Someday -- and a hard cap on how many items "Now" can hold. When it's full, adding something new means consciously swapping it for something alread

Practice LeetCode problems with automated spaced repetition scheduling.
@JoydeepNath007 · X

Portable memory that persists across Claude, ChatGPT, Cursor, and other AI assistants.
u/OrganicArgument2092 · Reddit
I shipped Lodekeep: portable memory for AI agents that follows you across Claude, Cursor, and ChatGPT Every new AI chat starts from zero. Claude, Cursor, ChatGPT all forget my stack, my decisions, the gotchas I already solved, so I kept re-pasting the same context every single session. I got sick of it and built Lodekeep. You capture a decision, preference, or lesson once, and it's recallable in every future session across every MCP client (Claude web + desktop, Claude Code, Cursor, Gemini

A browser-native intent memory for individual contributors. Never lose what you meant to do.
@Slaetapp · X

Knowl is an MCP memory server for Claude Code, Cursor and Codex. What your agents work out survives the session, and a change retires what it replaced — so the answer they read bac
@dat999zx · X
I built Knowl so my AI agents stop forgetting what's true. One memory they all read and write, always current. Runs entirely local — Claude Code, Codex, Cursor. Or for team sync, and reach the same memory from Claude and ChatGPT on the web.

Share context across AI agents so they remember your codebase and task history.
@dorikuio · X
AI agents have amnesia — Claude Code figures out the codebase, an hour later Codex starts from zero. So I built a shared memory + task board for every MCP agent — Claude Code, Codex, Cursor, Gemini CLI: Is this just my problem? Help me find out.

Persistent memory system for AI agents in Claude Code, Cursor, and other MCP-compatible applications.
FabianBeiner · HN
CMEM – Persistent Memory for AI Coding Agents

Lightweight VPS monitoring with real remote actions. See CPU, memory, and disk live, get alerted before things break, and restart or reboot straight from your phone.
@jasperissac · X
— a surprisingly simple way to keep an eye on VPS and website without constantly checking them yourself. Super useful for tracking changes, updates, or pages you care about. 👀

Constants is one workspace of tools for Claude and ChatGPT. Use your Gmail, Calendar, Sheets, and Notion, make video, music, and ads, and build tools for anything else. Connect onc
@arturf124 · X
Tools for ai assistants and having a blast doing. Demo:

Benchmark local coding models on consumer hardware to measure accuracy, latency, and throughput across 27 tasks.
u/Unfair_Association89 · Reddit
I built a reproducible benchmark for local coding models (Ollama, 27 tasks, live leaderboard) ran it on my 8GB card, here's what I found I kept eyeballing "vibes" to decide whether one quant of a coding model was actually better than another on my machine, so I built Sakura to get real numbers instead. What it does: - Points at any Ollama model and runs it through 27 hand-curated tasks: codegen, bugfix, SQL, refactor, systems design, protocol implementation, and terminal-agent episode