Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Local, private long-term memory for AI: verbatim, searchable, correctable. No LLM or API key.
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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"engram": {
"command": "uvx",
"args": [
"engram-chateau"
]
}
}
}在终端中运行这条命令
claude mcp add engram -- uvx engram-chateau粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"engram": {
"command": "uvx",
"args": [
"engram-chateau"
]
}
}
}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": {
"engram": {
"type": "stdio",
"command": "uvx",
"args": [
"engram-chateau"
]
}
}
}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。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
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。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
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 GitHub 账户 TushaeBXN 验证,该账户拥有此仓库
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
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
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 1 项适用的基础检查中通过了 1 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。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.10.5)于17天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
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。
Your AI forgets everything when the chat ends. Engram helps it remember.
Free, private, runs on your own computer, and keeps every word exactly as you wrote it.
On Monday you spend an hour with Claude working out why the login system leaks memory, and you decide to switch libraries. On Friday you open a new chat and ask *"why did we drop Passport again?"*
It has no idea. The conversation is gone, and so is the reasoning.
The same thing happens with everything you tell an AI: your sister's birthday, the bug you already fixed, the reason a setting is the way it is. Every new chat starts from zero.
Engram is a memory that outlasts the chat. It saves your notes, files and conversations, and when you ask a question later, it finds the right one, even if you phrase it completely differently.
Two ordinary notes go in:
notes/decisions.md We switched from Passport to Lucia on March 3 because
Passport sessions kept leaking memory under load. notes/personal.md My sister Maya's birthday is June 14. She loves anything with sunflowers.
engram mine notes --wing life
Days later, ask in your own words. None of these questions share a sentence with the notes:
$ engram search "why did we change the auth library"
1 life/notes We switched from Passport to Lucia on March 3 because Passport sessions kept leaking memory under load.
$ engram search "gift idea for Maya" 1 life/notes My sister Maya's birthday is June 14. She loves anything with sunflowers.
Hook it up to Claude and it does this by itself: Claude looks things up in Engram when it needs them, and Engram saves your Claude Code sessions automatically.
You need Python 3.9 or newer (3.11 to 3.14 is best). Check with python3 --version.
1. Install
pip install engram-chateau
On PyPI the package is called
engram-chateau, but the command you type is justengram. (A different, unrelated package already owns the nameengram.)
2. Give it something to remember
engram mine ~/Documents/notes --wing notes # any folder of notes, docs or code
The first run downloads a small language model (about 80 MB) that lets Engram understand meaning. After that, everything works offline.
3. Ask it something
engram search "what did I decide about the database"
That's all you need to try it.
Engram works with any app that speaks MCP, the standard way AI apps plug in tools. One command adds it:
engram connect cursor # or: claude-desktop, windsurf, vscode, gemini, codex, zed, lm-studio
engram connect all # every supported app on this computer engram connect # list them, with ✓ next to the ones you have
It adds Engram to that app's settings (keeping everything else, with a .bak backup) and tells you how to restart the app. Run it again any time; it changes nothing the second time.
| App | Setting it writes |
|---|---|
| Claude Desktop | claude_desktop_config.json |
| Cursor | ~/.cursor/mcp.json |
| Windsurf | ~/.codeium/windsurf/mcp_config.json |
| VS Code (Copilot agent mode) | your user mcp.json |
| Gemini CLI | ~/.gemini/settings.json |
| Codex CLI | ~/.codex/config.toml |
| Zed, LM Studio | prints the snippet to paste |
Every app then has 31 engram_* tools: recall, search, remember, correct an outdated memory, link a conclusion to its evidence, explain why a memory says what it says, a topic's history, a knowledge graph of people and facts, and more. On connect, Engram also tells the AI how to use them: check memory before answering anything that depends on past work, save decisions, and correct rather than contradict. (Apps decide whether to pass that guidance to the model; most current ones do.) Ask *"remember that we use tabs in this repo"*, *"what did we decide about auth?"* or *"we moved to PostgreSQL, update that"*.
Claude Code gets the most: memory that works without being asked.
engram connect claude-code # prints the one-line `claude mcp add` command
engram install-hooks --apply # then restart Claude Code
install-hooks adds three Claude Code hooks to ~/.claude/settings.json (your existing settings are kept, with a backup):
Preview what auto-recall would hand Claude with engram recall "your message". Run engram install-hooks without --apply to see the settings instead of applying them, or add --no-recall to skip auto-recall.
Any other MCP app: point it at the command engram-mcp (or python -m engram.mcp_server). Engram is also listed in the official MCP registry as io.github.TushaeBXN/engram.
Apps that don't speak MCP (Open WebUI, n8n, your own scripts) can use Engram over a small local web API:
engram serve # http://127.0.0.1:7742, the same tools and rules as MCP
Point the app at http://127.0.0.1:7742/openapi.json; every tool is described there. Or call it directly:
curl -s localhost:7742/v1/tools/engram_recall -H 'Content-Type: application/json' \
-d '{"message": "why did we drop Passport?"}'
Memories are private, so it is strict by default. It listens on localhost only, and refuses requests that look like they come from a web page or through a proxy. To reach it from another machine, use engram serve --host 0.0.0.0: that always requires a token (created on first use in ~/.engram/server/token, never printed), sent as Authorization: Bearer . engram serve --token requires one even on localhost. No CORS headers are ever sent, so a web page can't talk to it.
Teach any coding agent to use it. skills/engram/SKILL.md is a ready-made agent skill: when to recall, save and correct, and how to explain a conclusion. Install it with npx skills add TushaeBXN/engram (or copy the file).
Prefer uv, pipx or a guided setup?
uv tool install engram-chateau # or: pipx install engram-chateau
engram init ~/myproject # guided setup: your AI's identity, a default wing, then saves the project
Both put engram and engram-mcp on your PATH without touching your system Python.
🧑💻 Developers using Claude Code. Engram quietly saves the files Claude touches and the conversations behind them. Months later, *"why is the retry limit 7?"* brings back the actual discussion, not a guess.
🤖 People building an AI companion or agent. Give your bot a memory of its own: what it has learned about you, a diary, and a knowledge graph of people and facts (*"Kai works on Orion, since June"*). It all runs offline in a few lines of Python. Engram started life as exactly this, the memory of a personal companion app.
📚 Writers, researchers and note-takers. Point it at a folder of notes, an Obsidian vault, or Notion or Linear exports, and search across all of it by meaning: *"that idea I had about pricing tiers"*.
~/.engram/). No account, no cloud, no API key, no tracking.INV-20931), and understands time: *"two weeks ago"*, *"in June"*, *"on May 8"*.redact_secrets and API keys, tokens and passwords are blanked out before anything is written to disk.Engram files memories the way you'd organise a big house: one wing per person or project, a room per topic, a hall per kind of memory, and inside, drawers holding the original text.
Wing – a person or project ("myapp", "life")
└── Room – a topic ("auth-migration") └── Hall – the kind of memory (facts, events, discoveries, preferences, advice) └── Drawer – your original text, word for word
You don't have to manage any of this; Engram sorts things as it saves them. When you search, it weighs several clues together:
| Clue | What it does |
|---|---|
| Meaning | Finds text that means the same thing, even in different words |
| Exact words | A full-text index catches names, numbers and rare words the meaning search misses |
| Time | *"What did I buy two weeks ago?"* or *"what happened in June?"* favours memories from then |
| Passing remarks | Notices things you mentioned in passing (*"I've been sleeping badly"*) so later questions find them |
| Recency | Leans slightly toward newer memories; pinned ones never fade |
| Reranker *(optional)* | A small local model re-reads the top 20 and puts the best one first |
At the start of a session, Engram can also hand the AI a small "wake-up" note (who it is plus key facts: pinned ones first, then the newest, about 120 tokens by default), so it never starts completely cold.
In March you note that the app stores everything in SQLite. In April you move to PostgreSQL. Most memory tools now hold two contradicting notes and return whichever matches the question best.
In Engram, you (or Claude, or your agent) record the change once:
engram correct file-05aa607a "We只显示了开头部分;其余内容请在仓库中阅读