Renor

io.github.patrickpassosb由 GitHub 帳號 patrickpassosb 發布v1.0.1更新於 Oct 29, 2026

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

已驗證Streamable HTTP可網頁執行知識與記憶開發者工具

概覽

AI 產生的概覽

Renor 為 AI 程式開發助理提供共用的私有記憶,讓某個工作階段存下的事實與決策,能在之後被其他助理回想起來。

可以做什麼
  • 把決策、更正與事實存成可長期保留的純 Markdown 筆記。
  • 在開始重要工作前回想已存的脈絡,支援關鍵字搜尋,也可選用關鍵字加語意的混合搜尋。
  • 讓 Claude Code、Codex、Cursor、Grok、Gemini、VS Code、OpenCode 等多個助理共用同一份記憶。
  • 為每個助理設定各自的連線名稱,讓多個助理共用一份記憶並取得多助理工具。
  • 查看運作狀態並管理本機儲存,筆記放在資料夾中,搜尋索引使用 SQLite。
適用情境
適合同時使用多個程式開發助理、希望決策、根因與更正能跨工作階段延續而不必重複說明的情境。也適合想要自架、以檔案形式完全掌握記憶的個人或團隊。
執行需求
託管方式:使用 mcp.renor.cloud 遠端端點,需 OAuth 登入並在 renor.cloud 註冊帳號。自架方式:需要 Node.js 22.16 或更新版本,透過 npx renor-engine mcp 執行;筆記預設存於 ~/.renor,可用 VAULT_PATH 更改。混合搜尋可選用 OpenAI 或本機模型;多助理使用可選設 RENOR_CONNECTION_NAME。
安裝前請注意
託管方式會把記憶存放在 Renor 的伺服器上並需要帳號;自架方式則把筆記留在本機。匿名遙測預設開啟,可用 DO_NOT_TRACK=1 或關閉遙測指令停用。儲存的記憶可能包含專案細節,應避免存入密鑰;README 的記憶規則也明確要求不要儲存機密資訊。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Renor,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.patrickpassosb%2Frenor/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "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.

來源:README.md,提交 ef6e988

工具

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版本歷史

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

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