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Renor releases a cross-encoding agent shared memory engine

1 reports1 sources2 days agoUpdated

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Renor has released an MCP-based shared memory engine that allows the decisions, corrections, and facts recorded by one coding agent during a session to be read by other agents in the next session. The tool supports MCP clients such as Claude Code, Codex, Cursor, Grok, Gemini, VS Code, OpenCode, and Pi. There are two deployment options: the hosted version is described as the easiest path; the self-hosted version stores memory in a local folder and requires no account or API key. Running it requires Node.js 22.16 or later; if the version is too low, renor-engine will print a one-line notice and exit. Anonymous usage data is enabled by default and does not include text, names, or paths; a notice is shown on first run.

AI overview based on source reports · Updated 2 days ago

Latest developmentNov 5 01:06
Renor releases a cross-agent shared memory engine, connecting to Claude Code, Codex, Cursor, and others via MCP

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Nov 5
  1. Hacker News AI
    Show HN: Renor – one memory for all your AI agents

    Renor is a shared memory layer for coding agents over MCP that stores decisions, corrections and facts as plain Markdown you own, so what one agent learns in a session is recalled by others in the next. It offers a hosted path via `npx renor connect --client <name>` (claude-code, codex, cursor, grok, gemini, vscode, opencode or pi) and a self-hosted path via `npx -y renor-engine mcp` requiring Node.js 22.16 or later, with notes in ~/.renor and a SQLite search index rebuilt from the Markdown. The engine is Apache-2.0 (1.0.0 was AGPL-3.0), the CLI, SDKs and integrations are MIT, and anonymous telemetry is on by default unless disabled with `renor-engine telemetry off` or DO_NOT_TRACK=1.

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