
MarsNMe — Not Just Context. Continuity.
Claude.md is for context. MarsNMe is for continuity.
What it does
MarsNMe gives AI agents persistent memory across sessions. Two tiers: short-term context (auto-expiry) and long-term semantic recall via Jina embeddings + pgvector. 13 MCP tools. Multi-profile isolation. Works with Claude Desktop, Cursor, Warp. Apache 2.0, self-hosted. One npx command to start.
Does a similar job
all alternatives →- RGRecall: Give Claude memory with Redis-backed persistent contextOct 2025 · npmjs.com · ▲171
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…
- AgentmemoryMay 2026 · agent-memory.dev · ▲322
Persistent memory for Claude Code, Codex & coding agents

Second Brain for AIMay 2026 · github.com · ▲286Persistent memory for Claude, ChatGPT & Cursor. Free.

- SCStop Claude Code from forgetting everythingDec 2025 · github.com · ▲202
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…
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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