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Homestead Memory

제작자: fuckbigtech-ai버전 0.5.2i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.fuckbigtech-ai/homestead-memory

설치

개요

제작자가 쓴 설명(영어 원문)

Tamper-evident record of what your AI agent did, plus local-first verifiable memory.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio
  • 카테고리: 검색 및 AI 기억

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
  • 레지스트리에 입력해야 할 키가 나와 있지 않아요.

필요한 것

  • PyPIPython의 uv 설치(uvx 명령어용)

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "homestead-memory": {
      "command": "uvx",
      "args": [
        "homestead-memory",
        "mcp"
      ]
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add homestead-memory -- uvx homestead-memory mcp

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "homestead-memory": {
      "command": "uvx",
      "args": [
        "homestead-memory",
        "mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "homestead-memory": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "homestead-memory",
        "mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 fuckbigtech-ai 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

검색 및 AI 기억 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 5714개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 5714개 중 51%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 5714개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

Homestead Memory, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.5.2)은 38일 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Context7, Codebase Memory, Exa

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:↓ 주간 다운로드i★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Context7

Up-to-date docs for AI agents

제작자: upstash널리 사용됨↓ 97.3만/주★ 6.4만그저께 업데이트

컴퓨터 또는 클라우드

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

제작자: DeusData널리 사용됨↓ 1.8만/주★ 4.8만22일 전 업데이트

내 컴퓨터에서 실행

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

제작자: exa-labs널리 사용됨★ 5.2천2개월 전 업데이트

클라우드에서 실행✓ exa.ai

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

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 watch names 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 --deep now 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, run hsm checkpoint --export, publish the line somewhere they do not control, and check the ledger against it later with hsm 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

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