Alternatives
Products that do what SpecMem does
Unified Agent Experience & Pragmatic Memory for Coding Agent
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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
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Hi HN, TL;DR Memex is a cross-platform desktop app for vibe coding. Think ChatGPT + Claude Code rolled into one. Why we built it: We love chat tools like Perplexity and ChatGPT. We also love coding agents, like in Cursor and Windsurf. We don’t like that web-based app builders are opinionated about tech stack and we can’t run them locally. So, we built Memex to be a chat tool + coding agent that supports any tech stack. What it can do today: Claude Code-like coding. Agentic web search / research. Pre-built templates (e.g. fullstack, iOS, python + modal, etc). Inline data analysis + viz.…
2025 · memex.tech
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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
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Coding agents don't have long-term memory. But you do have months of full-fidelity agent transcripts stored on your machine. A simple solution that goes a long way: ingest those transcripts and logs into a structured SQLite database, then search them with ranked text match. Everything is fully local and doesn't require anything fancy like a graph database or hosted memory service. This is the idea behind ctx, a Rust CLI that handles the ingestion and searching. We give our agents a skill that tells them to reference past sessions before working in an area. Usually we do this through an…
Jul 2026 · github.com
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We’ve been working with automating coding agents in sandboxes as of late. It’s bewildering how poorly standardized and difficult to use each agent varies between each other. We open-sourced the Sandbox Agent SDK based on tools we built internally to solve 3 problems: 1. Universal agent API: interact with any coding agent using the same API 2. Running agents inside the sandbox: Agent Sandbox provides a Rust binary that serves the universal agent API over HTTP, instead of having to futz with undocumented interfaces 3. Universal session schema: persisting sessions is always problematic, since…
Jan 2026 · github.com
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This is a small library for giving an agent persistent memory without running any infrastructure. The whole store is one SQLite file, and the default install has no dependencies. I built it because whenever I wanted an agent to remember a handful of facts across sessions, the options were a hosted API, a vector database, or a framework, and that felt like too much for what is usually a few thousand short strings. The part I find most useful is that recall is deterministic, so you can write unit tests that assert what your agent remembers and run them in CI. I haven't seen that elsewhere and…
Aug 2026 · github.com
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Open Source Context Infrastructure for AI Agents
May 2026 · ravbyte-ai.github.io
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This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…
Jun 2026 · yourmemoryai.vercel.app
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Mar 2026 · agentmeet.net
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