Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Long-term memory for AI assistants: permanent, portable across clients, searchable and exportable.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://mcp.ambermem.com在终端中运行这条命令
claude mcp add --transport http amber https://mcp.ambermem.com粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"amber": {
"url": "https://mcp.ambermem.com"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"amber": {
"type": "http",
"url": "https://mcp.ambermem.com"
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://mcp.ambermem.com菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
服务器要求先登录,才会列出它的工具。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过域名 ambermem.com 验证(注册中心会核实域名所有权)
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
在 244 毫秒内响应(HTTP 401)
声明支持 OAuth 登录,你的 AI 应用可以带你去登录
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.1.1439)于昨天进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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.
One command. Works with any MCP-compatible client.
claude mcp add --transport http --scope user amber https://mcp.ambermem.com
Add to ~/.cursor/mcp.json (or %USERPROFILE%\.cursor\mcp.json on Windows):
{
"mcpServers": { "amber": { "url": "https://mcp.ambermem.com" } } }
Settings → Connectors → Create → URL: https://mcp.ambermem.com
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": { "amber": { "serverUrl": "https://mcp.ambermem.com" } } }
Add to .vscode/mcp.json:
{
"servers": { "amber": { "type": "http", "url": "https://mcp.ambermem.com" } } }
URL: https://mcp.ambermem.com | Transport: Streamable HTTP | Auth: OAuth 2.1 (auto-discovered)
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.
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".
Two settings, once. No tagging. No manual organization.
| Feature | Basic memory servers | Amber |
|---|---|---|
| Storage | One embedding per memory | Multiple semantic variants per fact |
| Search | Single vector lookup | Hybrid: vector + keyword + RRF fusion |
| Queries | Exact match only | Many phrasings per fact, matched semantically |
| Input | Stored as-is | Chunked into atomic facts, each independently searchable |
| Topics | Manual tags or none | Auto-grouped, matched semantically at search time |
| Privacy | Varies by server | No generative model reads your memories |
| Time | No temporal awareness | Natural language time parsing ("last week", "3 days ago") |
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
https://mcp.ambermem.comamber_send_feedback_to_developer tool directly.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.