Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Local, private long-term memory for AI: verbatim, searchable, correctable. No LLM or API key.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"engram": {
"command": "uvx",
"args": [
"engram-chateau"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add engram -- uvx engram-chateauIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"engram": {
"command": "uvx",
"args": [
"engram-chateau"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"engram": {
"type": "stdio",
"command": "uvx",
"args": [
"engram-chateau"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto TushaeBXN bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.10.5) kam vor 17 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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 "WeNur der Anfang wird gezeigt; den Rest findest du im Repo