Persistent, local, cross-IDE memory for AI agents — markdown source of truth, LanceDB-powered semantic search, zero cloud dependency
Persistent, local-first memory for your AI coding agents.
Stop re-explaining your architecture to Cursor, Zed, and Claude Code every single session.
Features • Install • Quick Start • CLI • MCP Tools • Architecture
You're developing a single project but switching between different agents — Cursor, Zed, Claude Code, OpenCode. Every one of them loses context of architectural decisions, system requirements, and user preferences the moment you close the tab. You end up re-explaining the same things over and over, or copy-pasting a stale CLAUDE.md between tools.
RMS Memory MCP bridges this gap: a single, isolated, centralized Markdown vault — perfectly structured for LLM consumption — that any MCP-compatible IDE can read from and write to.
------ 🗂️ Global Centralized Vaults Project context lives outside your repo — zero .mcp file pollution. 🔍 Hybrid Retrieval (LanceDB) Embedded Vector Search + Tantivy Full-Text Search for zero-fail context hits. 🌐 Multilingual Semantic Parsing fastembed-rs + multilingual-e5-small — native Russian & English understanding. 🌳 AST Markdown Chunker pulldown-cmark-based chunking keeps code blocks and lists bound to their parent heading. ⚙️ Dynamic Auto-Installer rms-memory install scans your system and wires itself into every supported IDE. 📜 Rules-as-Code Patching Non-destructive AST patching of .cursorrules, .zed/assistant.md, etc. Opt-in by default. 🧪 Dry-Run & Auditing --dry-run everywhere. Every write gets a rolling .bak backup. 🛡️ Ten-Point Resiliency GC, background sync, write-guard snapshots, macOS sandbox bypass, llms.txt export, path t
From the project README.
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Memory your agent can trust — every answer carries its source; when it doesn't know, it says so. Hermetic, local, MCP.
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