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Alternatives

Products that do what Tezcat – local-first AI recall in Obsidian via a remembrance agent does

Tezcat is a POC implementation of a remembrance agent (https://www.bradleyrhodes.com/Papers/remembrance.html) in Obsidian. It uses text embeddings and vector similarity search (or hybrid search) to do recall of fragments of notes that you've written in the past based on what you're writing right now. I don't like AI chat interfaces in knowledge management tools and I have been looking to implement something that would integrate better with the flow of actually writing. This operates best with Ollama on your machine, for a local-first experience, but can work with OpenAI…

  1. 1LA

    I built LocalGPT over 4 nights as a Rust reimagining of the OpenClaw assistant pattern (markdown-based persistent memory, autonomous heartbeat tasks, skills system). It compiles to a single ~27MB binary — no Node.js, Docker, or Python required. Key features: - Persistent memory via markdown files (MEMORY, HEARTBEAT, SOUL markdown files) — compatible with OpenClaw's format - Full-text search (SQLite FTS5) + semantic search (local embeddings, no API key needed) - Autonomous heartbeat runner that checks tasks on a configurable interval - CLI + web interface + desktop GUI - Multi-provider:…

    Feb 2026 · github.com

  2. 2OO

    Hi HN, Nick here. We’re launching OpenKnowledge (https://openknowledge.ai/), a “what you see is what you get” markdown editor that has direct integrations with Claude, Codex, and other agents. Available as MacOS app or Web UI+CLI. Fully free/local and OSS. We built this because we wanted a Notion-like experience for writing and sharing markdown files across our team. Obsidian is the best alternative we tried, but found it doesn’t have a true WYSWIG UI and it didn’t integrate well with Claude/Codex outside of community plugins. So we built OpenKnowledge. It takes…

    Jun 2026 · github.com

  3. 3
    Memori168

    Persistent memory from agent trace, not just conversation

    May 2026 · memorilabs.ai

  4. 4RL
  5. 5CO

    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

  6. 6
    ClawTab76

    Desktop app to manage 20+ AI coding agents at once

    Apr 2026

  7. 7CO

    We recently started to use agents to update some documentation across our codebase on a weekly basis, and everything quickly turned into cron jobs, logs, and terminal output. it worked, but was hard to tell what agents were doing, why something failed, or whether a workflow was actually progressing. We thought it would be more interesting to treat agents as long-lived workers with state and responsibilities and explicit handoffs. Something you can actually see and reason about, instead of just tailing logs. So we built Clawe, a small coordination layer on top of OpenClaw that lets agent…

    Feb 2026 · github.com

  8. 8CO

    So I've been building ClawMem, an open-source context engine that gives AI coding agents persistent memory across sessions. It works with Claude Code (hooks + MCP) and OpenClaw (ContextEngine plugin + REST API), and both can share the same SQLite vault, so your CLI agent and your voice/chat agent build on the same memory without syncing anything. The retrieval architecture is a Frankenstein, which is pretty much always my process. I pulled the best parts from recent projects and research and stitched them together: [QMD](https://github.com/tobi/qmd) for the…

    Mar 2026 · github.com

  9. 9

    Local AI with RAG, voice & WhatsApp. Open it and it works

    May 2026 · lmim.tech

  10. 10ML
  11. 11MO

    Hey HN! I'm Arindam, part of the team behind Memori (https://memori.gibsonai.com/). Memori adds a stateful memory engine to AI agents, enabling them to stay consistent, recall past work, and improve over time. With Memori, agents don’t lose track of multi-step workflows, repeat tool calls, or forget user preferences. Instead, they build up human-like memory that makes them more reliable and efficient across sessions. We’ve also put together demo apps (a personal diary assistant, a research agent, and a travel planner) so you can see memory in action. Current LLMs are stateless…

    2025 · github.com

  12. 12BA

    Writing is hard, and it's tempting to just let AI do the whole thing So I built an Obsidian plugin that keeps AI in its place Highlight a sentence, get some options, pick the one you like Sharpens your writing instead of automating it

    Jun 2026 · rephrasethis.co

  13. 13

    Sup HN! Dipanshu and Rushant here from Caspian. One is a functional programmer and the other has been deploying AI employees. Together we realized how agents have communication bottleneck. Given the coming agentic economy, we had a thought experiment on what can be the key infrastructure for agents as they get better. Our inspiration for solving for communications infra came from our own time spent just setting up comms while we were deploying open claw for companies plus we noticed about 15%+ of issues in Openclaw and Hermes were that of comms. So we abstracted the headache of reliable…

    16d ago · github.com

  14. 14BA

    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

  15. 15TA

    Hi HN, There’s been a lot of discussion lately around context graphs, decision traces, and how AI systems reason. One thing we kept running into: when AI agents make real decisions, the why behind those decisions often disappears. The context is scattered across prompts, tools, policies, and approvals. Logs show what happened, but not why it was allowed. TraceMem is an attempt to make decision context durable. It records the reasoning, authority, and context behind AI actions as a system of record, not as monitoring data, but as memory. Happy to share more details or answer questions. - Tommi

    Jan 2026 · tracemem.com

  16. 16WO

    We kept hitting the same wall building voice AI systems. Pipecat and LiveKit are great projects, genuinely. But getting it to production took us weeks of plumbing - wiring things together, handling barge-ins, setting up telephony, Knowledge base, tool calls, handling barge in etc. And every time we needed to tweak agent behavior, you were back in the code and redeploying. We just wanted to change a prompt and test it in 30 seconds. Thats why Vapi retell etc exist. So we wrote the entire code and open sourced it as a Visual drag-and-drop for voice agents ( same as vapi or n8n for voice).…

    Mar 2026 · github.com

  17. 17

    Cross-meeting memory for your Obsidian notes

    Jun 2026 · ibrh96.gumroad.com

  18. 18

    Gomaa — Autonomous Agent Memory OS. Persistent memory system for AI agents with Obsidian vault integration, hybrid RRF search, knowledge graphs, security gates, and MCP server. - M4F-S/gomaa

    14d ago · github.com

  19. 19SF
  20. 20AO

    Hi HN, I’m Akshay. I built AMP because I was tired of my AI agents having "amnesia" the moment I closed the terminal. Like many of you, I use Claude/Cursor daily. RAG is great for searching documentation, but it’s terrible for continuity. It chunks text blindly, losing the narrative. When I asked my agent "Why did we decide to use FastAPI last week?", it would hallucinate or just give me generic pros/cons because the specific context of our decision was lost in a vector soup. So I decided to build a proper *Hippocampus* for my agents. *What is it?* AMP is a local-first memory…

    Dec 2025 · github.com

  21. 21HD

    Hi guys. I have been working on Hitoku Draft, an open-source, voice-first AI assistant that runs entirely locally. I posted about it already, and now it has also transcription with voice editing. Looking for feedback, as I found that outside tech circles other people still do not use this tech much. It's context-aware, in the sense that it reads your screen, documents, and active app to understand what you're working on. You can ask about PDFs, reply to emails, create calendar events, use web search, editing text, all by voice. You can download a compiled version for free with the code…

    Jun 2026 · hitoku.me

  22. 22

    Local memory that follows you across AI tools

    9d ago · apps.microsoft.com

  23. 23
    OMem4

    Local-first work memory for your AI agents

    Jun 2026 · seacen.github.io

  24. 24

    Durable local-first memory for AI agents, with citations

    Jul 2026 · github.com

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