Alternatives
Products that do what Chronos7 does
Your AI forgets everything. Chronos builds on all of it.
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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…
Oct 2025 · npmjs.com
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I got tired of Claude Code forgetting all my context every time I open a new session: set-up decisions, how I like my margins, decision history. etc. We built a shared memory layer you can drop in as a Claude Code Skill. It’s basically a tiny memory DB with recall that remembers your sessions. Not magic. Not AGI. Just state. Install in Claude Code: /plugin marketplace add https://github.com/mutable-state-inc/ensue-skill /plugin install ensue-memory # restart Claude Code What it does: (1) persists context between sessions (2) semantic & temportal search (not just…
Dec 2025 · github.com
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2025 · contextch.at
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Hey HN! I built Retain as the evolution of claude-reflect (github.com/BayramAnnakov/claude-reflect). The original problem: I use Claude Code/Codex daily for coding, plus claude.ai and ChatGPT occasionally. Every conversation contains decisions, corrections, and patterns I forget existed weeks later. I kept re-explaining the same preferences. claude-reflect was a CLI tool that extracted learnings from Claude Code sessions. Retain takes this further with a native macOS app that: - Aggregates conversations from Claude Code, claude.ai, ChatGPT, and Codex CLI - Instant full-text…
Jan 2026 · github.com
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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
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Hi, I'm Daniel from Zep. I've integrated the Cursor IDE with Graphiti, our open-source temporal knowledge graph framework, to provide Cursor with persistent memory across sessions. The goal was simple: help Cursor remember your coding preferences, standards, and project specs, so you don't have to constantly remind it. Before this integration, Cursor (an AI-assisted IDE many of us already use daily) lacked a robust way to persist user context. To solve this, I used Graphiti’s Model Context Protocol (MCP) server, which allows structured data exchange between the IDE and Graphiti's temporal…
2025
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May 2026 · timeglass.ai
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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
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Hi HN, I’ve been building AI agents and copilots, and kept running into a frustrating problem: they don’t fail loudly, they forget things quietly. Users re-explain preferences, agents contradict earlier responses, and context resets without any clear visibility into why. I built Memograph CLI as a debugging tool to analyze conversation transcripts and show: - what the agent forgot - where continuity broke - contradictions and repeated context - estimated token waste due to re-prompting It works locally and supports plain text or JSON transcripts. Example: $ memograph Output: Cognitive Drift…
Feb 2026
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