memorylane

Love the local-first approach. The "just ask it to import my Notion" thing via browser automation is really nice. One thing I keep coming back to though - what if the tool could actually watch how you use your CRM and then suggest automations based on what it sees you doing repeatedly? I've been building something called MemoryLane (https://github.com/deusXmachina-dev/memorylane) that does exactly this - it captures screen activity, spots repeated workflows, and suggests automations. Works as an MCP server so you can plug it into Claude or Cursor. Instead of you having to describe what you want automated, it just watches and proposes stuff. Have you thought about adding something like pattern detection to denchclaw? Feels like it'd fit really well with the "everything app" direction. For us the most useful engine for executing skills and

Agent memory is one of those things that sounds straightforward until you actually try to build it. The filesystem metaphor makes a lot of sense as a starting point. I've been working on a slightly different angle with MemoryLane (https://github.com/deusXmachina-dev/memorylane) - instead of giving agents a place to write their own memories, it captures the user's screen activity and makes it queryable. So the agent gets context about what the human was doing, not just what the agent itself did. It plugs in via MCP so Claude Code / Cursor can just ask it stuff. I think there's something interesting in combining both - agent-vfs for the agent's own state, and something like MemoryLane for the human side. How do you think about that boundary between what the agent remembers vs what it knows about the user? We need to use vector DBs just beca

Cool demo. The tricky bit with browser workflow agents is figuring out which workflows to automate in the first place. Most people don't even realize they're doing the same thing over and over - they just do it. I've been building MemoryLane (https://github.com/deusXmachina-dev/memorylane) which comes at this from the other side - it records screen activity, spots repeated patterns with AI, and then tells you "hey you keep doing this, want to automate it?" Works as an MCP plugin for Claude/Cursor. Feels like pattern detection (finding what to automate) + browser agents like yours (actually doing the automation) is the right combo. Are you thinking about the discovery side at all, or mostly focused on execution?

Hey Parker, this is really cool! Thanks for sharing. Have you tried using the entire CLI? It might also be a tool which you could compose into your workflow to have better memory of what the agents themselves did in the repo. Btw, I built something similar to solve the context problem for most of my laptop-based activity. It's slightly more heavyweight (electron app ingesting screenshots) - that being said I took many similar design decisions (local embeddings, sqlite with vector search and FTS hybrid, MCP extension to claude). Feel free to check it out: https://github.com/deusXmachina-dev/memorylane

all of those questions can be answered with https://github.com/deusXmachina-dev/memorylane

We built a desktop app that screenshots your screen periodically, runs it through a vision model, and stores the context locally. Then it pipes everything into your AI tools via MCP. Most people we showed it to started using it to generate timesheets. Any ideas for what else this could do are welcome! Website: https://trymemorylane.com/ GitHub: https://github.com/deusXmachina-dev/memorylane

Desktop app that: - Takes screenshots of your activity - Summarizes with vision models, then deletes the screenshot - Stores text summaries locally - Exposes it to AI tools via MCP Demo: https://www.loom.com/share/513b213e82d14323999e419fa434576d Feedback welcome, especially around privacy/security and technical approach

Nice work - the daily-log-first approach resonates. We hit the same "re-onboarding Claude every morning" problem and went a different direction with MemoryLane (https://github.com/deusXmachina-dev/memorylane): it sits in the background capturing your activity (screenshots + OCR + summaries) and makes that context available to any AI chat via MCP. Different tradeoff - Total Recall is curated (daily logs) and lean, MemoryLane for now captures broadly and relies on search to surface what's relevant. I think they are complementary: your write gate keeps project knowledge tight, broad context with search fills in the "wait, what tab/webpage was that" gaps. We applied to this batch (YC S26), still waiting on Apple notarization before a wider release. Happy to chat if anyone's curious about the screen-context approach.