Renor

io.github.patrickpassosb由 GitHub 账号 patrickpassosb 发布v1.0.1更新于 Oct 29, 2026

Private memory for AI agents: save and recall facts across Claude Code, Codex, Cursor and ChatGPT.

已验证Streamable HTTP可网页运行知识与记忆开发者工具

概览

AI 生成的概览

Renor 为 AI 编程助手提供共享的私有记忆,让一个会话中保存的事实和决策能被其他助手在后续会话中回忆。

可以做什么
  • 把决策、纠正和事实保存为可长期保留的纯 Markdown 笔记。
  • 在开始重要工作前回忆已存上下文,支持关键词搜索,也可选用关键词加语义的混合搜索。
  • 让 Claude Code、Codex、Cursor、Grok、Gemini、VS Code、OpenCode 等多个助手共用同一份记忆。
  • 通过为每个助手设置独立连接名,让多个助手共用一份记忆并获得多助手工具。
  • 查看运行状态并管理本地存储,笔记保存在文件夹中,搜索索引使用 SQLite。
适用场景
适合同时使用多个编程助手、希望决策、根因和纠正能跨会话延续而不必重复说明的场景。也适合希望自托管、以文件形式完全掌控记忆的个人或团队。
运行要求
托管方式:使用 mcp.renor.cloud 远程端点,需 OAuth 登录并在 renor.cloud 注册账号。自托管方式:需要 Node.js 22.16 或更高版本,通过 npx renor-engine mcp 运行;笔记默认存于 ~/.renor,可用 VAULT_PATH 更改。混合搜索可选接入 OpenAI 或本地模型;多助手使用可选设置 RENOR_CONNECTION_NAME。
安装前请注意
托管方式会把记忆存放在 Renor 的服务器上并需要账号;自托管方式则把笔记留在本机。匿名遥测默认开启,可用 DO_NOT_TRACK=1 或关闭遥测命令停用。保存的记忆可能包含项目细节,应避免存入密钥;README 中的记忆规则也明确要求不要保存机密信息。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Renor,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.patrickpassosb%2Frenor/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "mcpServers": {
    "renor": {
      "type": "http",
      "url": "https://mcp.renor.cloud/mcp"
    }
  }
}

README

[Renor]

Shared memory for coding agents, over MCP.

What one agent learns in a session, every agent knows in the next.

How it works

  1. Tell one agent once: a decision, a root cause, a correction.
  2. Renor saves it as plain Markdown you own.
  3. Every agent recalls it in its next session: Claude Code, Codex, Cursor, Grok, Gemini, VS Code, OpenCode, Pi or any MCP client.

Quickstart

Two ways in. Both take under a minute.

Hosted: the easiest path

bash
npx renor connect --client claude-code

--client is claude-code, codex, cursor, grok, gemini, vscode, opencode or pi. One command adds Renor to that app, signs you in through the app's own flow (no token to copy), writes the memory rule below, and ends with a live check that your workspace answers. Search is hybrid (keywords and meaning). Sign up at renor.cloud.

Self-hosted: the private path

Your memory stays in a folder on your machine. No account, no API key. You need Node.js 22.16 or later (22.16+ or 24+); on an older Node, renor-engine prints one line saying so and exits.

bash
claude mcp add --scope user renor-local -- npx -y renor-engine mcpcodex mcp add renor-local -- npx -y renor-engine mcp

Restart the agent. The first start downloads about 12 MB, and the first Renor call works about 3 seconds after an empty start. Notes go to ~/.renor (set VAULT_PATH to use another folder).

Then add the memory rule to the agent's instructions file, so it saves on its own.

Cursor or VS Code, one click:

[Add to Cursor] [Add to VS Code]

Grok. Grok starts project servers only in a folder it trusts, so register Renor in the project:

bash
grok mcp add --scope project renor -- npx -y renor-engine mcp

Trust the folder in Grok, then restart Grok. To check it: ask Grok to save a real decision from your project, restart Grok, and ask about it in the new session. To turn telemetry off, set DO_NOT_TRACK=1 in the environment Grok runs in. Paste the memory rule into the project's AGENTS.md.

Any other MCP client: the command is npx with the arguments -y renor-engine mcp (stdio).

Check it works:

bash
npx renor-engine status

Then tell your agent a real decision ("remember that the orders service uses Postgres 16"), start a new session, and ask about it.

Running it on a server or with Docker: docs/self-hosting.md.

Several agents on one memory: start each with its own RENOR_CONNECTION_NAME and they get the multi-agent ("hive") tools (details).

The memory rule

Five lines that make agents save decisions, corrections and facts on their own. In our Grok test (grok-4.7, renor-engine 1.4.0, 3 Nov 2026), agents with the rule saved in 8 of 8 sessions and the next session recalled 5 of 5 project facts.

renor connect writes it for you. Self-hosted, paste it into ~/.claude/CLAUDE.md (Claude Code), ~/.codex/AGENTS.md (Codex) or the project's AGENTS.md (Grok):

md
## Renor memory
Renor is connected to this app and remembers across sessions.- Before deciding anything non-trivial, recall first: one get_context call is usually enough.- Save with remember when the user makes a decision, corrects you, or states a fact that should outlive this chat. Include the reason.- Save the specific value (a port, a name, a path), not a summary of it.- Do not save secrets, or things that are already in the code.

Self-hosted, the local tools are search, remember_fact and note; agents map the rule onto them (tool list).

What runs on your machine

  • Your memory is plain Markdown in one folder you own. Edit it with anything; back it up like any folder.
  • SQLite holds the search index, next to the notes. It is rebuilt from the Markdown at any time.
  • No embedding model needed. Search is by keyword; when the exact words miss, it retries with word stems. Hybrid search (keywords and meaning) is the hosted default; self-hosters can opt in to OpenAI or a local model (details).
  • Small: a 1.8 MB package, about 5 MB installed. About 143 MB of memory with 1,000 saved memories.
  • Telemetry: anonymous usage numbers (never text, names or paths) are on by default, with a notice on first run. renor-engine telemetry off or DO_NOT_TRACK=1 turns them off. Your memory text is never shared unless you say yes to that separately. Every field: docs/TELEMETRY.md.

Benchmarks

BenchmarkRenorSetup
LongMemEval-S98.4% (492/500)Deep search, off by default
LongMemEval-S94.4% (472/500)Default settings
LoCoMo (categories 1 to 4)96.7% (1,489/1,540)Deep search
BEAM 128K / 1M / 10M76.2 / 74.7 / 60.2Deep search, score out of 100
ConvoMem88.4% (191/216)Default search, 100 conversations per memory

Claude Opus 5.5 answers LongMemEval, LoCoMo and BEAM; DeepSeek V4.1 Flash answers ConvoMem (a research run). One run each, Oct 2026. Deep search is top-K 50 with a 4,000-token budget (RENOR_TOPK_SCALES_BUDGET=1). Judges and methods for every run: renor.cloud/research.

Build from source

You need Node.js 22.16 or later and git.

bash
git clone https://github.com/renorai/renor-engine.gitcd renor-enginenpm ci && npm run buildnode scripts/smoke-self-hosted.mjs

The last command starts the MCP server in a temporary folder, saves one fact, finds it again and ends with PASS: self-hosted stdio MCP can remember and retrieve a current fact. It never touches your notes. Downloaded a ZIP instead of cloning? Build with RENOR_BUILD_COMMIT=0000000 npm run build. Connecting a local build to each agent: docs/self-hosting.md.

Learn more

Docs · Self-hosting, servers and Docker · Every setting · Telemetry

License and contributing

The engine is Apache-2.0 (LICENSE); 1.0.0 was released under AGPL-3.0; 1.1.0 and later are Apache-2.0; files imported from the upstream project stay ISC (NOTICE, UPSTREAM.md). The renor CLI, the SDKs and the integrations are MIT.

Contributions are welcome: CONTRIBUTING.md has setup, tests and good first issues. Sign off each commit with the DCO (git commit -s); there is no CLA. Report vulnerabilities privately as described in SECURITY.md.

If Renor saves you re-explaining, a ⭐ helps other developers find it.

来源:README.md,提交 ef6e988

工具

0
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版本历史

2
  1. v1.0.1最新Oct 29, 2026
  2. v1.0.0Oct 16, 2026

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