Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Self-hosted AI memory server. Persistent memory on your hardware, not the cloud.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
STRATA_URL, STRATA_API_KEYNecesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"strata": {
"command": "npx",
"args": [
"-y",
"strata-mcp-server"
],
"env": {
"STRATA_URL": "your-value",
"STRATA_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add strata --env STRATA_URL=your-value --env STRATA_API_KEY=your-value -- npx -y strata-mcp-serverCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"strata": {
"command": "npx",
"args": [
"-y",
"strata-mcp-server"
],
"env": {
"STRATA_URL": "your-value",
"STRATA_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"strata": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"strata-mcp-server"
],
"env": {
"STRATA_URL": "your-value",
"STRATA_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
STRATA_URL envSTRATA_API_KEY envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub agenerationforwordz-tech, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (2.2.0) llegó al registro hace 7 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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.
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.
v2.0 taught Strata who's talking. v2.2 teaches it to scale, audit, and remember your past.
read / write / delete / admin / kill permissions. You stop sharing one key across every tool. Manage them from /admin/agents./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./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.strata system user owns the database with mode 600. SSH users can no longer bypass the API by editing the SQLite file directly.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:
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.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.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.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.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.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.
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.
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).
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.
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:
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
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
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';"
sudo -u postgres psql -d strata_db -f strata_pg_schema.sql
export STRATA_DB_BACKEND=postgresql export STRATA_PG_PASSWORD=your-password-here
python server.py
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.
| Feature | SQLite | PostgreSQL |
|---|---|---|
| Concurrent writers | 1 (write queue) | Unlimited |
| Similarity search | numpy in Python | pgvector HNSW in-database |
| Full-text search | FTS5 | tsvector (weighted) |
| Scale target | < 10K thoughts | 1M+ thoughts |
| Setup complexity | Zero | Moderate |
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
mkdir -p data cp demo/strata.db data/strata.db
STRATA_DEMO_MODE=true python server.py
⏱️ First install takes 5–15 minutes.
pip install -r requirements.txtdownloads about 700 MB of binary wheels for the embedding model runtime (fastembed,onnxruntime,numpy,transformerstokenizer 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 withpip install -r requirements.txt --progress-bar onif you want to watch the byte count tick up.
Open these in your browser:
| URL | What you see |
|---|---|
http://localhost:4320/dashboard | Web dashboard — login with blank password (demo mode) |
http://localhost:4320/constellation | 3D constellation viewer with all 666 thoughts laid out in sacred-geometry clusters |
http://localhost:4320/admin/agents | Per-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.
A few Windows-specific gotchas worth knowing about:
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.)
Solo se muestra el principio; lee el resto en el repo