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Strata

제작자: agenerationforwordz-tech버전 2.2.0i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.agenerationforwordz-tech/strata

설치

개요

제작자가 쓴 설명(영어 원문)

Self-hosted AI memory server. Persistent memory on your hardware, not the cloud.

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: Streamable HTTP
  • 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.
  • 직접 입력할 값: STRATA_URL, STRATA_API_KEY

필요한 것

  • npmNode.js 설치(npx 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": {
    "strata": {
      "command": "npx",
      "args": [
        "-y",
        "strata-mcp-server"
      ],
      "env": {
        "STRATA_URL": "your-value",
        "STRATA_API_KEY": "your-value"
      }
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add strata --env STRATA_URL=your-value --env STRATA_API_KEY=your-value -- npx -y strata-mcp-server

실행하기 전에 빈 값을 채워 주세요.

Cursor에서 열기

또는 설정을 직접 복사하기

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

{
  "mcpServers": {
    "strata": {
      "command": "npx",
      "args": [
        "-y",
        "strata-mcp-server"
      ],
      "env": {
        "STRATA_URL": "your-value",
        "STRATA_API_KEY": "your-value"
      }
    }
  }
}

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": {
    "strata": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "strata-mcp-server"
      ],
      "env": {
        "STRATA_URL": "your-value",
        "STRATA_API_KEY": "your-value"
      }
    }
  }
}

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.

직접 입력할 값

  • STRATA_URL env
    URL of your Strata server (e.g. http://10.0.0.18:4320/mcp)
  • STRATA_API_KEY env
    Your agent API key from /admin/agents

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 7일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 agenerationforwordz-tech 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 7286개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 7286개 중 10%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 7286개 중 100%와 같거나 더 좋아요

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

자주 묻는 질문

Strata, 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(2.2.0)은 7개월 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 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:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Context7

제작자: upstash

Up-to-date docs for AI agents

컴퓨터 또는 클라우드★ 64,224MIT어제 업데이트
설치

Codebase Memory

제작자: DeusData

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

내 컴퓨터에서 실행★ 48,148MIT21일 전 업데이트
설치

Exa

제작자: exa-labs

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

클라우드에서 실행★ 5,213MIT지난달 업데이트
설치

제작자의 README

README 열기

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

STRATA v2.2

This repository is superseded by [SOLUM](https://github.com/agenerationforwordz-tech/Solum).

SOLUM is the actively developed version of this project: PostgreSQL + pgvector instead of SQLite,

a larger tool set, and numerous fixes not present here. New users should start with SOLUM.

This repository remains available for reference.

Self-hosted AI memory server. Your thoughts, your hardware, your data.

Why Strata?

Your AI forgets everything the moment the session ends. Strata fixes that. It gives any MCP-compatible AI a persistent memory that lives on YOUR hardware - not in the cloud, not on someone else's server. Search by meaning, attach real files, and run it all on a Raspberry Pi.

What's new in v2.2

v2.0 taught Strata who's talking. v2.2 teaches it to scale, audit, and remember your past.

  • Per-agent API keys - every AI agent gets its own key with granular read / write / delete / admin / kill permissions. You stop sharing one key across every tool. Manage them from /admin/agents.
  • Global MCP kill switch - one toggle that locks every agent out of MCP, REST, and /api/*. Any agent with write or kill permission can pull the brake; only a human admin can flip it back on. Built for the moment a tool goes rogue.
  • 3D Constellation viewer - watch your brain think in real time at /constellation. Sacred-geometry layout (Flower of Life background, dodecahedron clusters, Fibonacci sphere distribution), per-agent colors, live activity stream, and a kill-switch indicator that desaturates the whole scene when MCP is offline.
  • Per-agent identity colors - each agent gets a color from a curated palette, editable from the admin panel. Colors flow through the constellation viewer so you can tell at a glance which agent is doing what.
  • Encryption at rest (optional) - SQLCipher AES-256 encryption with key in a root-only file. Dormant by default; flip on with one env var and a setup script when your threat model needs it.
  • File-level hardening (optional) - dedicated strata system user owns the database with mode 600. SSH users can no longer bypass the API by editing the SQLite file directly.
  • Demo mode - run a public demo with STRATA_DEMO_MODE=true and the dashboard accepts blank passwords (the login screen still renders so visitors can see the auth feature exists).

New in v2.2:

  • PostgreSQL + pgvector backend — SQLite is still the default for quick demos, but set STRATA_DB_BACKEND=postgresql for production. PostgreSQL handles concurrent multi-agent writes natively (no more write queue), and pgvector does similarity search IN the database with HNSW indexes. Scales to 1 million+ thoughts.
  • CSV audit log — every agent action is logged to daily CSV files in data/audit/. Full replay tape: who searched what, which thoughts came back, how long it took. This is the transparency layer — trace exactly how an AI built its understanding of your data. View via GET /api/audit.
  • Pre-Strata history (negative IDs) — import your memories from BEFORE you installed Strata using capture_legacy. These get negative IDs (-1, -2, -3...) and live in the same constellation alongside your current thoughts. Your AI memory doesn't start at install day — it reaches back as far as you want. Click "THOUGHTS" in the constellation viewer to toggle between current and historical views.
  • 10 thought types — expanded from 8 types with clear descriptions that teach AI agents WHEN to use each one. Added idea (brainstorms, not yet decided) and observation (patterns noticed, no conclusions drawn). The agent protocol now spells out type selection so every new user's constellation is balanced.
  • Updated agent protocol — strata_status now teaches agents about all 10 types, negative ID history, the audit log, and outcome loop tracking. No CLAUDE.md needed — the protocol IS the onboarding.
  • Constellation camera fix — clicking a star flies the camera past it and looks back, keeping the origin star visible in the background as an anchor.
  • Demo mode improvements — agent creation and MCP kill switch now work without an admin key in demo mode.

Plus the v1 features you already know: semantic search, file vault, dedup protection, password+seed-phrase dashboard auth, dark theme, runs on a Pi.

I built this because I got tired of my AI tools forgetting everything between sessions. STRATA gives any MCP-compatible AI (Claude Code, Codex CLI, whatever comes next) a persistent brain that lives on YOUR machine. Not in the cloud. Not on someone else's server. Yours.

It runs on a Raspberry Pi 4B. Seriously. The whole thing - semantic search, file storage, embeddings - runs on a $55 computer with 4GB of RAM.

What it does

  • Search by meaning - ask for "money stuff" and it finds your notes about Bitcoin, investments, and budgets. Not keyword matching. Actual understanding.
  • File vault - attach real files to your thoughts. Code, documents, project archives. The thought is your index, the vault holds the goods.
  • Auto-tagging - write about Docker? It tags it. Mention a URL? Tagged. You don't have to organize anything manually.
  • Dedup protection - tries to save something you already saved? It catches it and warns you.
  • Access tracking - see which memories actually get used vs which ones just sit there.
  • Admin-only deletion - AI can read and write memories, but it CANNOT delete anything without your explicit admin key. Your data, your control.

Why I built it this way

Regular databases search by keywords. If you stored "switching careers" but search for "new job", you get nothing.

STRATA converts every thought into a 768-dimensional vector that captures what it *means*. Similar ideas land near each other in that vector space. So "switching careers" and "new job" and "career change" all find each other.

The model runs locally through ONNX Runtime (not PyTorch - that thing eats 1.5GB just to import on ARM). Total RAM for the embedding model is about 100-150MB, and it unloads after 5 minutes of idle time.

The file vault

This is what makes STRATA more than a note-taking app.

You capture a thought about a project. Then you attach the actual source files to it. Later, when you or your AI searches for that topic, you get the thought AND a list of every file attached to it. The AI picks which files it needs and pulls just those - it doesn't load your whole drive into memory.

Files are organized on disk like this:

data/vault/

my-laptop/ 2026-03/ 42/ server.py config.py my-desktop/ 2026-03/ 55/ training_data.csv

Organized by device and month. You can browse it manually if you want. Files up to 1GB, text files capped at 5MB when returned to AI (so it doesn't blow up the context window).

Pre-Strata history (negative IDs)

Your AI memory doesn't have to start at install day. Import your past:

# Via MCP tool

capture_legacy( content="Decided to self-host everything after the cloud bill hit $400/mo", thought_type="decision", tags=["infrastructure", "self-hosting"], original_date="2024-06-15", source="pre-strata" )

Legacy thoughts get negative IDs (-1, -2, -3...) while live thoughts use positive IDs. Both are fully searchable — they live in the same vector space. The constellation viewer has a toggle: click "THOUGHTS" to dim current stars and highlight your history.

CSV audit log

Every agent interaction is logged to daily CSV files in data/audit/:

data/audit/

audit_2026-04-19.csv audit_2026-04-20.csv ...

Each row records:

  • timestamp — when the operation completed (UTC)
  • agent_name — which agent made the call
  • agent_key_hint — masked API key (enough to identify, not enough to use)
  • action — what happened (capture_thought, semantic_search, etc.)
  • detail — search query or content preview
  • thought_ids — which thoughts were touched
  • result_count — how many results came back
  • response_ms — operation duration

Query today's log via REST: GET /api/audit?limit=50

Override the directory: STRATA_AUDIT_DIR=/your/path Disable entirely: STRATA_AUDIT_ENABLED=false

PostgreSQL backend (production)

SQLite works great for getting started and single-user setups. For production with multiple agents hitting Strata simultaneously, switch to PostgreSQL:

# Install PostgreSQL 17 + pgvector

sudo apt install postgresql-17 postgresql-17-pgvector

Create the database and user

sudo -u postgres createuser strata sudo -u postgres createdb strata_db -O strata sudo -u postgres psql -c "ALTER USER strata PASSWORD 'your-password-here';"

Run the schema (creates tables, indexes, triggers)

sudo -u postgres psql -d strata_db -f strata_pg_schema.sql

Set the backend

export STRATA_DB_BACKEND=postgresql export STRATA_PG_PASSWORD=your-password-here

Start Strata — it auto-detects the backend

python server.py

Migrating from SQLite to PostgreSQL

If you already have thoughts in SQLite:

python migrate_to_pg.py

This migrates all thoughts, embeddings, history, agent keys, and profiles. Your SQLite database is preserved as a backup.

Why PostgreSQL?
FeatureSQLitePostgreSQL
Concurrent writers1 (write queue)Unlimited
Similarity searchnumpy in Pythonpgvector HNSW in-database
Full-text searchFTS5tsvector (weighted)
Scale target< 10K thoughts1M+ thoughts
Setup complexityZeroModerate

Try the demo first (60 seconds, no setup)

The repo ships with a pre-populated demo database: 666 curated thoughts about Strata itself, 3 sample agents with palette colors, ready to explore. No mining, no seed data hunt, no thinking about what to capture first — just clone, drop the demo DB into place, and see the constellation populated.

git clone https://github.com/agenerationforwordz-tech/strata.git

cd strata

python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate pip install -r requirements.txt

Drop the curated demo dataset into place

mkdir -p data cp demo/strata.db data/strata.db

Run with demo mode so blank passwords work for visitors

STRATA_DEMO_MODE=true python server.py

⏱️ First install takes 5–15 minutes. pip install -r requirements.txt downloads about 700 MB of binary wheels for the embedding model runtime (fastembed, onnxruntime, numpy, transformers tokenizer support). Don't kill the install if it appears stuck — it's downloading binaries in the background. Subsequent installs reuse the venv and take seconds. Run with pip install -r requirements.txt --progress-bar on if you want to watch the byte count tick up.

Open these in your browser:

URLWhat you see
http://localhost:4320/dashboardWeb dashboard — login with blank password (demo mode)
http://localhost:4320/constellation3D constellation viewer with all 666 thoughts laid out in sacred-geometry clusters
http://localhost:4320/admin/agentsPer-agent key management with the 3 sample agents (all disabled by default — enable one or create your own to start using Strata)

See demo/README.md for the full demo dataset details, including how to regenerate your own.

Windows install notes

A few Windows-specific gotchas worth knowing about:

  • Git "dubious ownership" error on the D: drive. If you clone Strata to D:\ or any non-system drive, Git may refuse to operate on the repo with fatal: detected dubious ownership in repository. Fix:
  git config --global --add safe.directory 'D:/Claude Code Projects/strata'

(Replace the path with wherever you cloned.)

  • **PowerShell env vars use `$en

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