Amber

com.ambermem由 ambermem.com 发布官方发布者v1.1.1439更新于 Nov 5, 2026

Long-term memory for AI assistants: permanent, portable across clients, searchable and exportable.

已验证Streamable HTTP可网页运行知识与记忆AI 与机器学习

概览

AI 生成的概览

Amber 是一个托管式长期记忆服务,让 AI 助手跨对话、跨客户端保存、检索并导出关于你的信息。

可以做什么
  • 在日常对话中保存记忆,自动拆分为带主题和日期的原子事实
  • 按语义、关键词和自然语言时间范围检索记忆
  • 管理记忆库与账户,包括导出和删除数据
  • 向开发者发送反馈或通知
适用场景
如果你希望助手在不同会话和不同 MCP 客户端之间记住偏好、决定和项目背景,并且愿意把它的工具设为常开、再添加一条自定义指令让它主动保存记忆,就值得添加。
运行要求
远程 Streamable HTTP 端点,使用 OAuth 2.1 登录,无需本地安装包。90 天试用期后需 PayPal 账户付费。还需两项客户端设置:一条让助手主动保存记忆的自定义指令,以及把 Amber 工具设为始终可用。
安装前请注意
记忆文本会发送给第三方嵌入服务,且仅提供托管服务,无法自托管。试用期后每月 2.99 美元,通过 PayPal 扣款。助手会写入、检索并可能删除已保存的个人数据,README 还建议让它不经询问就保存记忆,因此应留意存了什么,并按需导出或删除。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Amber,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/com.ambermem%2Famber/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": {
    "amber": {
      "type": "http",
      "url": "https://mcp.ambermem.com/"
    }
  }
}

README

Amber

Long-term memory for AI assistants.

Amber is an MCP server that gives any AI assistant persistent, searchable memory across conversations. Your AI remembers preferences, decisions, project context, and personal details - once it is connected and the two required settings below are on.

Just talk normally. Amber stores what matters and finds it when relevant.

Quick Install

One command. Works with any MCP-compatible client.

Claude Code / Claude Desktop

bash
claude mcp add --transport http --scope user amber https://mcp.ambermem.com

Cursor

Add to ~/.cursor/mcp.json (or %USERPROFILE%\.cursor\mcp.json on Windows):

json
{  "mcpServers": {    "amber": {      "url": "https://mcp.ambermem.com"    }  }}

ChatGPT

Settings → Connectors → Create → URL: https://mcp.ambermem.com

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

json
{  "mcpServers": {    "amber": {      "serverUrl": "https://mcp.ambermem.com"    }  }}

VS Code (GitHub Copilot)

Add to .vscode/mcp.json:

json
{  "servers": {    "amber": {      "type": "http",      "url": "https://mcp.ambermem.com"    }  }}

Any MCP client

URL: https://mcp.ambermem.com | Transport: Streamable HTTP | Auth: OAuth 2.1 (auto-discovered)

Required: two settings

Adding the URL is not enough on its own. Without these two settings, most assistants use Amber only when you explicitly say "remember this", and their built-in memory quietly takes everything else, so Amber stays nearly empty.

  1. Add this to your AI's custom instructions / personal preferences (Claude personal preferences, ChatGPT custom instructions, Cursor rules, etc.):

    Whenever something worth remembering comes up - a life event, a decision, a preference, something I learned or realized, or anything about who I am - save it to Amber (my memory) without asking. Treat normal conversation as a source of memories, not only when I say "remember this".

  2. Keep Amber's tools always available. In your client's tool or MCP settings, set Amber to "always on" rather than on-demand, so your AI can reach it the instant a memory comes up.

How It Works

  1. You talk to your AI normally. Amber stores important facts in the background.
  2. Next conversation, your AI searches Amber automatically when context would help.
  3. Memory improves over time. The more you use it, the better it gets.

Two settings, once. No tagging. No manual organization.

What Makes Amber Different

FeatureBasic memory serversAmber
StorageOne embedding per memoryMultiple semantic variants per fact
SearchSingle vector lookupHybrid: vector + keyword + RRF fusion
QueriesExact match onlyMany phrasings per fact, matched semantically
InputStored as-isChunked into atomic facts, each independently searchable
TopicsManual tags or noneAuto-grouped, matched semantically at search time
PrivacyVaries by serverNo generative model reads your memories
TimeNo temporal awarenessNatural language time parsing ("last week", "3 days ago")

Technical Details

  • 29 MCP tools (14 memory, 13 account, 2 feedback/notification)
  • Hybrid retrieval pipeline: vector search + full-text search + Reciprocal Rank Fusion
  • Multi-variant embeddings: every fact is stored with several paraphrases (at least 5; a store with fewer is rejected), which is the main thing that makes it findable later
  • No generative model reads your memories: your assistant does the chunking, the topics and the phrasings. Memory text is sent only to an embedding endpoint (a vector model, not a chat model), so no chat model is ever shown what you store
  • Atomic facts: a conversation becomes individually searchable facts rather than one blob, each with its own subjects, topics and dates
  • Temporal search: "what did I say last week?" resolves to a real date range rather than a keyword match
  • Automatic topic grouping: memories are grouped by topic, and a search for "work" also finds "career" and "job"
  • Async processing: storage completes in the background, never blocking your conversation

Pricing

  • 90-day free trial - no charge, cancel anytime
  • $2.99/month after trial, via PayPal
  • Cancel instantly - ask your AI to cancel, or cancel through PayPal directly
  • No lock-in - export all your data as JSON anytime

Privacy

  • No email collected
  • No marketing, no spam
  • Data isolated per user (separate database)
  • PayPal handles all payment info
  • Full export + account deletion available
  • GDPR compliant (data minimization by design)

Architecture

Amber runs on Cloudflare Workers (zero cold starts, global edge deployment) with Turso databases (one per user, full isolation). Your assistant does the chunking, the topics and the phrasings, so no generative model is ever shown what you store; memory text is sent only to OpenAI's embedding endpoint.

For full technical documentation: ambermem.com/llms.txt

Links

FAQ

Will it slow my AI down? No. Storage is async (background). Search adds <1 second.

What if Amber shuts down? Export all your data as JSON anytime. Your data is always yours.

Do I need a PayPal account? Currently yes. PayPal handles both identity and billing. More login options coming soon.

Is my data safe? Each user gets a completely isolated database. No data is shared between users. Amber has no access to your PayPal payment details.

Can I self-host? Not currently. Amber is a managed service. We handle the infrastructure, scaling, and LLM costs so you don't have to.

来源:README.md,提交 e907aa2

工具

0
该服务器需要登录,因此 SourceWeft 无法在没有账号的情况下读取其工具,也未收录。已连接账号所能看到的内容可能因账号及其权限而异。

版本历史

13
  1. v1.1.1439最新Nov 5, 2026
  2. v1.1.1438Nov 3, 2026
  3. v1.1.1430Oct 11, 2026
  4. v1.1.1427Oct 11, 2026
  5. v1.1.1423Oct 6, 2026
  6. v1.1.1405Oct 1, 2026
  7. v1.1.1404Sep 29, 2026
  8. v1.1.1402Sep 27, 2026
  9. v1.1.1400Sep 27, 2026
  10. v1.1.1399Sep 27, 2026
  11. v1.1.1398Sep 27, 2026
  12. v1.1.1384Sep 23, 2026
  13. v1.1.1295Sep 16, 2026

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