Homestead Memory
Überblick
Beschreibung vom Entwickler (englisches Original)
Tamper-evident record of what your AI agent did, plus local-first verifiable memory.
Die drei Säulen von PopNx MCP
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
- Stimmen der NutzeriNoch keine BewertungenBewertungen starten in einem späteren Schritt zusammen mit Benutzerkonten
- Unsere Basischecksi1 von 1 bestandenAnhand öffentlicher Informationen geprüft; Code noch nicht gescannt
- NutzungiGanz neu↓ 26/Wo. · ★ –
Was du damit machen kannst
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
- Verbindung: Läuft auf deinem Computer
- Transport: stdio
- Kategorie: Suche & KI-Gedächtnis
Installation
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Bevor du installierst
- Basischecks: 1 von 1 bestanden
- Läuft auf deinem Computer mit den Rechten deines Benutzerkontos (Dateien, Netzwerk, Apps).
- Die Registry nennt keinen Schlüssel zum Eintragen.
Du brauchst
- PyPIuv für Python installiert (für den Befehl uvx)
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": {
"homestead-memory": {
"command": "uvx",
"args": [
"homestead-memory",
"mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add homestead-memory -- uvx homestead-memory mcpOder kopier die Einstellungen selbst
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"homestead-memory": {
"command": "uvx",
"args": [
"homestead-memory",
"mcp"
]
}
}
}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.
Oder kopier die Einstellungen selbst
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"homestead-memory": {
"type": "stdio",
"command": "uvx",
"args": [
"homestead-memory",
"mcp"
]
}
}
}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.
Was er kann
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Basischecksi
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 8. Nov. 2026
- ✓ Bestanden
Entwickler passt zum Repo
Der Registry-Name wurde mit dem GitHub-Konto fuckbigtech-ai bestätigt, dem das Repo gehört
- … Noch nicht geprüft
Wird noch gepflegt
Dieses Repo haben wir noch nicht von GitHub gelesen
- … Noch nicht geprüft
Hat eine Lizenz
Dieses Repo haben wir noch nicht von GitHub gelesen
- – Nicht zutreffend
Endpunkt antwortet
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
- – Nicht zutreffend
Anmeldung mit OAuth
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
- … Noch nicht geprüft
Keine versteckten Anweisungen in Tool-Beschreibungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Im Vergleich mit anderen in Suche & KI-Gedächtnisi
- Mehr Sterne als 0 % der anderen 5688 Server in dieser Kategorie
- Neuer in der Registry veröffentlicht als 52 % der anderen 5688 Server in dieser Kategorie
- Basischecks gleich gut wie oder besser als bei 100 % der anderen 5688 Server in dieser Kategorie
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Häufige Fragen
Ist Homestead Memory sicher?
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.
Welche Schlüssel oder Codes braucht er?
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Läuft er auf meinem Computer oder in der Cloud?
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).
Wird er noch gepflegt?
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.5.2) kam vor 38 Tagen in die Registry.
Welche Apps können ihn nutzen?
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
Was kann ich stattdessen nutzen?
In derselben Kategorie: Context7, Codebase Memory, Exa
Alternativen
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:↓ Downloads pro Wochei★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Codebase Memory
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Exa
Connect AI agents to Exa for web search, content fetching, and multi-step research.
README vom Entwickler
README öffnen
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.
homestead-memory
Stop renting your mind.
A tamper-evident record of what your AI agent actually did, in a local file, that someone who does not trust you can verify. Tamper-evident, not tamper-proof: what it defends against and what it does not.
Agents fail quietly. The run reports success, the tool returns 200, and the thing you asked for did not happen. There is usually no record to contradict it. This keeps one, and every entry is hash-chained to the one before it, so *see it catch a forged record, live:*
pip install homestead-memory # Python 3.10+, macOS / Linux / Windows
hsm watch --demo
0 14:02:11 Bash npm test
1 14:02:19 Read src/api/billing.py
2 14:02:24 Edit src/api/billing.py
#
② now someone edits record 1…
!! chain break at index 1: hash_mismatch
record content does not match its own hash (edited in place)
exit 1 · gate it in CI like a test
Got `No matching distribution found`? macOS still ships Python 3.9 as its built-in
python3, and this needs 3.10+. Nothing is wrong with the package. Either use a newer
Python, or skip installing entirely:
uvx --from homestead-memory hsm watch --demo
(uv fetches a suitable Python for you.)
Record your own agent
hsm hook --install # prints a Claude Code hook; you paste it, nothing is edited for you
hsm watch # what your agent did, in order
Every entry is hash-chained to the one before it, so editing, deleting, or reordering any record breaks every hash after it. hsm watch reports the break at the exact index and exits non-zero. Sign it and a wholly rebuilt chain is caught too.
Both phases are recorded, which is what makes it evidence rather than a log. The hook captures the decision before a tool runs and the outcome after. A record of outcomes alone shows what happened; it cannot show that anything was authorised first. As the IETF Agent Audit Trail draft puts it, "a denial that is only logged after execution provides no evidence that the denial was enforced".
hsm export --format aat # the same ledger as draft-sharif-agent-audit-trail-01
That draft maps explicitly to EU AI Act Article 12, and this emits it alongside the native format rather than replacing it, so nothing already on disk changes. Where we differ we say so: it specifies ECDSA P-256, which the AAT export uses, while the native EvidencePack stays Ed25519 so its verifier can remain standard-library only and a recipient needs nothing installed.
Know this before you rely on the AAT export. That draft is an individual Internet-Draft, not an adopted standard: it has no working group behind it and carries the usual notice that it "is not endorsed by the IETF". Its author has also filed IPR disclosure 7558, covering revisions 00 and 01 in full, declaring "Reasonable and Non-Discriminatory License to All Implementers with Possible Royalty/Fee". RAND with a possible fee is not royalty-free, and this package is MIT, which grants you no patent licence. We ship the export because interoperability is worth having and we have asked the author to clarify what implementers are taking on. Until there is an answer, treat --format aat as a convenience rather than something to build a compliance programme on. The native ledger and EvidencePack carry no such disclosure, and they are what the rest of this README argues for.
What it costs you: about 124ms per tool call (median; 138ms p95, measured on an M3 Pro with a 4KB tool response). Since 0.4.0 the hook records both phases, so it runs as a fresh process twice per call, once before your tool runs and once after: about 61ms and 63ms respectively. On a 100-call session that is roughly 12 seconds spread across the run. Almost all of it is Python interpreter and import startup rather than the recording itself. If that is too much for your loop, do not install the hook: the number is here so you can decide before you find out.
Earlier releases documented 68ms, which was correct when only PostToolUse was recorded. Recording the decision phase is what makes the ledger evidence of enforcement rather than of observation, and it costs a second process. Stating the higher number rather than the one that flatters us is the same reason the rest of these figures are here.
This is a file, not a platform. Agent observability tools are far richer than this and they want a deployment: the self-hosted ones document a production floor of several services and roughly 16 GB of RAM. This is pip install, one hook line, and a JSONL file on your disk. Different job. If you need dashboards, evals, and span analytics, use one of those. If you want a record you can grep and prove, use this.
Secret-shaped values are redacted and payloads truncated to a 200-character head, with a SHA-256 of the full original kept so the evidence survives redaction. That is a mitigation, not a guarantee: no pattern list is complete.
hsm export --evidence # a pack anyone can verify with no install at all
The pack carries the records, the signature, the public key, an integrity report, and a standard-library verifier a third party can read in full and run. It states what it does NOT prove, including that a signature only establishes origin if you already know which key to expect.
What this defends against, and what it does not
Tamper-evident, not tamper-proof. The difference matters, so here it is plainly.
It catches:
- A record edited in place. The hash stops matching and
hsm watchnames the index. - A record deleted or reordered. Every hash after it breaks.
- A silently dropped write. Drops are recorded and reported, never swallowed.
- A whole chain rebuilt from scratch by someone who recomputed every hash, provided you ran `hsm checkpoint`, you pin the expected signer, and they do not hold your key. All three matter. A checkpoint verified without a pinned key is self-asserted: it checks the signature against whichever key sits beside it, so a rebuilt chain re-signed with the attacker's own key also passes.
hsm verify --deepnow says so when no key is pinned.
hsm verify --deep --signer <your pubkey> # or the checkpoint is self-asserted
- Anything altered after you handed someone an EvidencePack, which they can check with no install and nothing from us.
A checkpoint covers its prefix, not the future. Records appended after your last checkpoint can be replaced with a correctly re-chained forgery and still verify, because a signature cannot cover records that did not exist when it was made. hsm verify tells you how many records are uncovered. Re-checkpoint often, or that tail grows.
It does not catch:
- An attacker who holds your signing key. The key lives at
~/.config/homestead-memory/ed25519_key, on the same machine as the ledger. Anyone who can rewrite the file can usually read that key, re-sign the rewrite, and pass. If that is your threat model, runhsm checkpoint --export, publish the line somewhere they do not control, and check the ledger against it later withhsm checkpoint --verify. A head hash reveals nothing about the records, so publishing one leaks nothing. - A tool that lies. See below.
- Anything that never reached the ledger at all, such as a hook you did not install.
hsm checkpoint # sign the current head
hsm checkpoint --export # one line to publish where an attacker cannot reach hsm checkpoint --verify # check this ledger against a line you published earlier
hsm watch reports how much of the ledger the checkpoint covers, and fails if the checkpoint no longer verifies. Everything appended since your last checkpoint is uncovered, so re-checkpoint often.
It records what your harness reported
The hook receives what the harness says a tool did. It is not independent observation.
If a tool reports success while doing nothing, that is precisely the failure this exists to catch, because you get a durable record of the claim and can compare it against reality. But if a tool reports something false about *what* it did, the ledger will faithfully record a hash-chained, signed falsehood.
The record proves the record was not altered. It does not make the harness truthful.
Why not just OpenTelemetry, or signed logs, or Langfuse
Reasonable questions, and mostly they are different jobs.
- OpenTelemetry gives you far richer tracing and an ecosystem this does not have. It is not built to be tamper-evident, and spans usually leave the machine. Use both if you want: they answer "what happened, in detail" and this answers "can I prove it was not edited".
- Signing your log files gets you most of the way, and if you already do it you may not need this. The differences are per-record chaining, so a single altered line is located rather than the whole file being invalidated, and a pack whose verifier a recipient runs with nothing installed.
- Langfuse, Braintrust, Phoenix are observability platforms with dashboards, evals and span analytics this will never have. They also want a deployment. The self-hosted ones document a production floor of several services and roughly 16 GB of RAM. This is one hook line and a JSONL file. If you want dashboards, use them.
The narrow thing this does that those do not: produce a record a third party can verify without trusting you, without installing anything, and without the data leaving your machine.
And the memory it reads is yours too
The same tool owns the memory your agent reads and writes: plain markdown you can read, git diff, and walk away with. It catches its own rot, tampering, and poisoning with mechanical checks rather than an LLM judge, scores it 0 to 100, and exits non-zero so it gates CI and cron like a test suite.
npm install -g @tobilu/qmd@2.1.0 # optional hybrid retrieval runtime
hsm verify --demo
① a clean vault ✅ MEMORY INTACT — 100/100
② rot is planted… 🔴 ROT DETECTED — 0/100
🔴 [self_contradiction] the note argues with itself about its own status
🔴 [uncited_claim] a distilled claim has no source citation
🔴 [dangling_citation] a cited source no longer exists
⚠️ [broken_link] a reference points at a note that isn't there
That scoring is RotBench, published as an open spec so the number is r
Nur der Anfang wird gezeigt; den Rest findest du im Repo