Ombre Brain
一个给提供给Claude 用的长期情绪记忆系统。基于 Russell 效价/唤醒度坐标打标,Obsidian 做存储层,MCP 接入,带遗忘曲线。
A long-term emotional memory system for Claude. Tags memories using Russell's valence/arousal coordinates, stores them as Obsidian-compatible Markdown, connects via MCP, and has a forgetting curve.

它是什么 / What is this
Claude 没有跨对话记忆。每次对话结束,之前聊过的所有东西都会消失。
Ombre Brain 给了它一套持久记忆——不是那种冷冰冰的键值存储,而是带情感坐标的、会自然衰减的、像人类记忆一样会遗忘和浮现的系统。
Claude has no cross-conversation memory. Everything from a previous chat vanishes once it ends.
Ombre Brain gives it persistent memory — not cold key-value storage, but a system with emotional coordinates, natural decay, and forgetting/surfacing mechanics that loosely mimic how human memory works.
核心特点 / Key features:
- 情感坐标打标 / Emotional tagging: 每条记忆用 Russell 环形情感模型的 valence(效价)和 arousal(唤醒度)两个连续维度标记。不是"开心/难过"这种离散标签。
Each memory is tagged with two continuous dimensions from Russell's circumplex model: valence and arousal. Not discrete labels like "happy/sad".
- 自然遗忘 / Natural forgetting: 改进版艾宾浩斯遗忘曲线。不活跃的记忆自动衰减归档,高情绪强度的记忆衰减更慢。
Modified Ebbinghaus forgetting curve. Inactive memories naturally decay and archive. High-arousal memories decay slower.
- 权重池浮现 / Weight pool surfacing: 记忆不是被动检索的,它们会主动浮现——未解决的、情绪强烈的记忆权重更高,会在对话开头自动推送。
Memories aren't just passively retrieved — they actively surface. Unresolved, emotionally intense memories carry higher weight and get pushed at conversation start.
- Obsidian 原生 / Obsidian-native: 每个记忆桶就是一个 Markdown 文件,YAML frontmatter 存元数据。可以直接在 Obsidian 里浏览、编辑、搜索。自动注入
[[双链]]。
Each memory bucket is a Markdown file with YAML frontmatter. Browse, edit, and search directly in Obsidian. Wikilinks are auto-injected.
- API 降级 / API degradation: 脱水压缩和自动打标优先用廉价 LLM API(DeepSeek 等),API 不可用时自动降级到本地关键词分析——始终可用。
Dehydration and auto-tagging prefer a cheap LLM API (DeepSeek etc.). When the API is unavailable, it degrades to local keyword analysis — always functional.
边界说明 / Design boundaries
官方记忆功能已经在做身份层的事了——你是谁,你有什么偏好,你们的关系是什么。那一层交给它,Ombre Brain不打算造重复的轮子。
Ombre Brain 的边界是时间里发生的事,不是你是谁。它记住的是:你们聊过什么,经历了什么,哪些事情还悬在那里没有解决。两层配合用,才是完整的。
每次新对话,Claude 从零开始——但它能从 Ombre Brain 里找回跟你有关的一切。不是重建,是接续。
Official memory already handles the identity layer — who you are, what you prefer, what your relationship is. That layer belongs there. Ombre Brain isn't trying to duplicate it.
Ombre Brain's boundary is *what happened in time*, not *who you are*. It holds conversations, experiences, unresolved things. The two layers together are what make it feel complete.
Each new conversation starts fresh — but Claude can reach back through Ombre Brain and find everything that happened between you. Not a rebuild. A continuation.
架构 / Architecture
Claude ←→ MCP Protocol ←→ server.py
│
┌───────────────┼───────────────┐
│ │ │
bucket_manager dehydrator decay_engine
(CRUD + 搜索) (压缩 + 打标) (遗忘曲线)
│
Obsidian Vault (Markdown files)5 个 MCP 工具 / 5 MCP tools:
| 工具 Tool | 作用 Purpose |
|---|---|
breath | 浮现或检索记忆。无参数=推送未解决记忆;有参数=关键词+情感检索 / Surface or search memories |
hold | 存储单条记忆,自动打标+合并相似桶 / Store a single memory with auto-tagging |
grow | 日记归档,自动拆分长内容为多个记忆桶 / Diary digest, auto-split into multiple buckets |
trace | 修改元数据、标记已解决、删除 / Modify metadata, mark resolved, delete |
pulse | 系统状态 + 所有记忆桶列表 / System status + bucket listing |
安装 / Setup
环境要求 / Requirements
- Python 3.11+
- 一个 Obsidian Vault(可选,不用也行,会在项目目录下自建
buckets/)
An Obsidian vault (optional — without one, it uses a local buckets/ directory)
步骤 / Steps
git clone https://github.com/P0lar1zzZ/Ombre-Brain.git
cd Ombre-Brain
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install -r requirements.txt复制配置文件并按需修改 / Copy config and edit as needed:
cp config.example.yaml config.yaml如果你要用 API 做脱水压缩和自动打标(推荐,效果好很多),设置环境变量: If you want API-powered dehydration and tagging (recommended, much better quality):
export OMBRE_API_KEY="your-api-key"支持任何 OpenAI 兼容 API。在 config.yaml 里改 base_url 和 model 就行。 Supports any OpenAI-compatible API. Just change base_url and model in config.yaml.
接入 Claude Desktop / Connect to Claude Desktop
在 Claude Desktop 配置文件中添加(macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):
Add to your Claude Desktop config:
{
"mcpServers": {
"ombre-brain": {
"command": "python",
"args": ["/path/to/Ombre-Brain/server.py"],
"env": {
"OMBRE_API_KEY": "your-api-key"
}
}
}
}接入 Claude.ai (远程) / Connect to Claude.ai (remote)
需要 HTTP 传输 + 隧道。可以用 Docker: Requires HTTP transport + tunnel. Docker setup:
echo "OMBRE_API_KEY=your-api-key" > .env
docker-compose up -ddocker-compose.yml 里配好了 Cloudflare Tunnel。你需要自己在 ~/.cloudflared/ 下放凭证和路由配置。 The docker-compose.yml includes Cloudflare Tunnel. You'll need your own credentials under ~/.cloudflared/.
指向 Obsidian / Point to Obsidian
在 config.yaml 里设置 buckets_dir: Set buckets_dir in config.yaml:
buckets_dir: "/path/to/your/Obsidian Vault/Ombre Brain"不设的话,默认用项目目录下的 buckets/。 If not set, defaults to buckets/ in the project directory.
配置 / Configuration
所有参数在 config.yaml(从 config.example.yaml 复制)。关键的几个: All parameters in config.yaml (copy from config.example.yaml). Key ones:
| 参数 Parameter | 说明 Description | 默认 Default |
|---|---|---|
transport | stdio(本地)/ streamable-http(远程) | stdio |
buckets_dir | 记忆桶存储路径 / Bucket storage path | ./buckets/ |
dehydration.model | 脱水用的 LLM 模型 / LLM model for dehydration | deepseek-chat |
dehydration.base_url | API 地址 / API endpoint | https://api.deepseek.com/v1 |
decay.lambda | 衰减速率,越大越快忘 / Decay rate | 0.05 |
decay.threshold | 归档阈值 / Archive threshold | 0.3 |
merge_threshold | 合并相似度阈值 (0-100) / Merge similarity | 75 |
敏感配置用环境变量: Sensitive config via env vars:
OMBRE_API_KEY— LLM API 密钥OMBRE_TRANSPORT— 覆盖传输方式OMBRE_BUCKETS_DIR— 覆盖存储路径
衰减公式 / Decay Formula
$$final\_score = time\_weight \times base\_score$$
$$base\_score = Importance \times activation\_count^{0.3} \times e^{-\lambda \times days} \times (base + arousal \times boost)$$
时间系数(乘数,优先级最高)/ Time weight (multiplier, highest priority):
| 距今天数 Days since active | 时间系数 Weight |
|---|---|
| 0–1 天 | 1.0 |
| 第 2 天 | 0.9 |
| 之后每天约降 10% | max(0.3, 0.9 × e^{-0.2197 × (days-2)}) |
| 7 天后稳定 | ≈ 0.3(不归零) |
importance: 1-10,记忆重要性 / memory importanceactivation_count: 被检索的次数,越常被想起衰减越慢 / retrieval count; more recalls = slower decaydays: 距上次激活的天数 / days since last activationarousal: 唤醒度,越强烈的记忆越难忘 / arousal; intense memories are harder to forget- 已解决的记忆权重降到 5%,沉底等被关键词唤醒 / resolved memories drop to 5%, sink until keyword-triggered
pinned=true的桶:不衰减、不合并、importance 锁定 10 /pinnedbuckets: never decay, never merge, importance locked at 10
给 Claude 的使用指南 / Usage Guide for Claude
CLAUDE_PROMPT.md 是写给 Claude 看的使用说明。放到你的 system prompt 或 custom instructions 里就行。
CLAUDE_PROMPT.md is the usage guide written for Claude. Put it in your system prompt or custom instructions.
工具脚本 / Utility Scripts
| 脚本 Script | 用途 Purpose |
|---|---|
write_memory.py | 手动写入记忆,绕过 MCP / Manually write memories, bypass MCP |
migrate_to_domains.py | 迁移平铺文件到域子目录 / Migrate flat files to domain subdirs |
reclassify_domains.py | 基于关键词重分类 / Reclassify by keywords |
reclassify_api.py | 用 API 重打标未分类桶 / Re-tag uncategorized buckets via API |
test_smoke.py | 冒烟测试 / Smoke test |
部署 / Deploy
Render

⚠️ 免费层不可用:Render 免费层不支持持久化磁盘,服务重启后记忆数据会丢失,且会在无流量时休眠。必须使用 Starter($7/mo)或以上才能正常使用。 Free tier won't work: Render free tier has no persistent disk — all memory data is lost on restart. It also sleeps on inactivity. Starter plan ($7/mo) or above is required.
项目根目录已包含 render.yaml,点击按钮后:
- (可选)设置
OMBRE_API_KEY:任何 OpenAI 兼容 API 的 key,不填则自动降级为本地关键词提取 - (可选)设置
OMBRE_BASE_URL:API 地址,支持任意 OpenAI 化地址,如https://api.deepseek.com/v1/http://123.1.1.1:7689/v1/http://your-ollama:11434/v1 - Render 自动挂载持久化磁盘到
/opt/render/project/src/buckets - 部署后 MCP URL:
https://.onrender.com/mcp
render.yaml is included. After clicking the button:
- (Optional)
OMBRE_API_KEY: any OpenAI-compatible key; omit to fall back to local keyword extraction - (Optional)
OMBRE_BASE_URL: any OpenAI-compatible endpoint, e.g.https://api.deepseek.com/v1,http://123.1.1.1:7689/v1,http://your-ollama:11434/v1 - Persistent disk auto-mounts at
/opt/render/project/src/buckets - MCP URL after deploy:
https://.onrender.com/mcp
Zeabur
💡 Zeabur 的定价模式:Zeabur 是「买 VPS + 平台托管」,你先购买一台服务器(最低腾讯云新加坡 $2/mo、火山引擎 $3/mo),Volume 直接挂在该服务器上,数据天然持久化,无丢失问题。另需订阅 Zeabur 管理方案(Developer $5/mo),总计约 $7-8/mo 起。 Zeabur pricing model: You buy a VPS first (cheapest: Tencent Cloud Singapore ~$2/mo, Volcano Engine ~$3/mo), then add Zeabur's Developer plan ($5/mo) for management. Volumes mount directly on your server — data is always persistent, no cold-start data loss. Total ~$7-8/mo minimum.
步骤 / Steps:
- 创建项目 / Create project
- 打开 zeabur.com → 购买一台服务器 → New Project → Deploy from GitHub - 先 Fork 本仓库到自己 GitHub 账号,然后在 Zeabur 选择 你的用户名/Ombre-Brain - Zeabur 会自动检测到根目录的 Dockerfile 并使用 Docker 方式构建 - Go to zeabur.com → buy a server → New Project → Deploy from GitHub - Fork this repo first, then select your-username/Ombre-Brain in Zeabur - Zeabur auto-detects the Dockerfile in root and builds via Docker
- 设置环境变量 / Set environment variables(服务页面 → Variables 标签页)
- OMBRE_API_KEY(可选)— LLM API 密钥,不填则自动降级为本地关键词提取 - OMBRE_BASE_URL(可选)— API 地址,如 https://api.deepseek.com/v1
> ⚠️ 不需要手动设置 OMBRE_TRANSPORT 和 OMBRE_BUCKETS_DIR,Dockerfile 里已经设好了默认值。Zeabur 对单阶段 Dockerfile 会自动注入控制台设置的环境变量。 > You do NOT need to set OMBRE_TRANSPORT or OMBRE_BUCKETS_DIR — defaults are baked into the Dockerfile. Zeabur auto-injects dashboard env vars for single-stage Dockerfiles.
- 挂载持久存储 / Mount persistent volume(服务页面 → Volumes 标签页)
- Volume ID:填 ombre-buckets(或任意名) - 挂载路径 / Path:/app/buckets - ⚠️ 不挂载的话,每次重新部署记忆数据会丢失 - ⚠️ Without this, memory data is lost on every redeploy
- 配置端口 / Configure port(服务页面 → Networking 标签页)
- Port Name:web(或任意名) - Port:8000 - Port Type:HTTP - 然后点 Generate Domain 生成一个 xxx.zeabur.app 域名 - Then click Generate Domain to get a xxx.zeabur.app domain
- 验证 / Verify
- 访问 https://.zeabur.app/health,应返回 JSON - Visit https://.zeabur.app/health — should return JSON - 最终 MCP 地址 / MCP URL:https://.zeabur.app/mcp
常见问题 / Troubleshooting:
| 现象 Symptom | 原因 Cause | 解决 Fix |
|---|---|---|
| 域名无法访问 / Domain unreachable | 没配端口 / Port not configured | Networking 标签页加 port 8000 (HTTP) |
| 域名无法访问 / Domain unreachable | OMBRE_TRANSPORT 未设置,服务以 stdio 模式启动,不监听任何端口 / Service started in stdio mode — no port is listened | Variables 标签页确认设置 OMBRE_TRANSPORT=streamable-http,然后重新部署 |
| 构建失败 / Build failed | Dockerfile 未被识别 / Dockerfile not detected | 确认仓库根目录有 Dockerfile(大小写敏感) |
| 服务启动后立刻退出 | OMBRE_TRANSPORT 被覆盖为 stdio | 检查 Variables 里有没有多余的 OMBRE_TRANSPORT=stdio,删掉即可 |
| 重启后记忆丢失 / Data lost on restart | Volume 未挂载 | Volumes 标签页挂载到 /app/buckets |
使用 Cloudflare Tunnel 或 ngrok 连接 / Connecting via Cloudflare Tunnel or ngrok
ℹ️ 自 v1.1 起,server.py 在 HTTP 模式下已自动添加 CORS 中间件,无需额外配置。 Since v1.1, server.py automatically enables CORS middleware in HTTP mode — no extra config needed.
使用隧道连接时,确保以下条件满足: When connecting via tunnel, ensure:
- 服务器必须运行在 HTTP 模式 / Server must use HTTP transport
OMBRE_TRANSPORT=streamable-http python server.py或 Docker:
docker-compose up -d- 在 Claude.ai 网页版添加 MCP 服务器 / Adding to Claude.ai web
- URL 格式 / URL format: https://.trycloudflare.com/mcp - 或 ngrok / or ngrok: https://.ngrok-free.app/mcp - 先访问 /health 验证连接 / Verify first: https:///health should return {"status":"ok",...}
- 已知限制 / Known limitations
- Cloudflare Tunnel 免费版有空闲超时(约 10 分钟),系统内置保活 ping 可缓解但不能完全消除 - Free Cloudflare Tunnel has idle timeout (~10 min); built-in keepalive pings mitigate but can't fully prevent it - ngrok 免费版有请求速率限制 / ngrok free tier has rate limits - 如果连接仍失败,检查隧道是否正在运行、服务是否以 streamable-http 模式启动 - If connection still fails, verify the tunnel is running and the server started in streamable-http mode
| 现象 Symptom | 原因 Cause | 解决 Fix |
|---|---|---|
| 网页版无法连接隧道 URL / Web can't connect to tunnel URL | 服务以 stdio 模式运行 / Server in stdio mode | 设置 OMBRE_TRANSPORT=streamable-http 后重启 |
| 网页版无法连接隧道 URL / Web can't connect to tunnel URL | 旧版 server.py 缺少 CORS 头 / Missing CORS headers | 拉取最新代码,CORS 已内置 / Pull latest — CORS is now built-in |
/health 返回 200 但 MCP 连不上 / /health 200 but MCP fails | 路径错误 / Wrong path | MCP URL 末尾必须是 /mcp 而非 / |
| 隧道连接偶尔断开 / Tunnel disconnects intermittently | Cloudflare Tunnel 空闲超时 / Idle timeout | 保活 ping 已内置,若仍断开可缩短隧道超时配置 |
Session Start Hook(自动 breath)
部署后,如果你使用 Claude Code,可以在项目内激活自动浮现 hook: .claude/settings.json 已配置好 SessionStart hook,每次新会话或恢复会话时自动触发 breath,把最高权重未解决记忆推入上下文。
仅在远程 HTTP 模式下有效(OMBRE_TRANSPORT=streamable-http)。本地 stdio 模式下 hook 会安静退出,不影响正常使用。
可以通过 OMBRE_HOOK_URL 环境变量指定服务器地址(默认 http://localhost:8000),或者设置 OMBRE_HOOK_SKIP=1 临时禁用。
If using Claude Code, .claude/settings.json configures a SessionStart hook that auto-calls breath on each new or resumed session, surfacing your highest-weight unresolved memories as context. Only active in remote HTTP mode. Set OMBRE_HOOK_SKIP=1 to disable temporarily.
License
MIT
