MemoraEu

Personal memory layer for AI assistants. Store, search and recall preferences, decisions and facts — available from any MCP-compatible client.

GitHub

MemoraEU Server

🇫🇷 Français · 🇬🇧 English

Français

MemoraEU donne à votre IA une mémoire persistante et chiffrée — souveraine, zero-knowledge, hébergée en Europe. Compatible Claude, Cursor, Windsurf, ChatGPT, GitHub Copilot, n8n via MCP. Auto-hébergement gratuit (AGPL v3) ou cloud géré EU

Ce que ça fait

MemoraEU est un serveur de mémoire auto-hébergeable pour les assistants IA. Il implémente le Model Context Protocol (MCP) pour que n'importe quel client MCP (Claude, Cursor, Windsurf, ChatGPT, GitHub Copilot, n8n…)

Recherche sémantique propulsée par Qdrant + embeddings (Ollama ou Mistral)
Multi-utilisateur / multi-org avec auth JWT
Transports MCP : Legacy SSE (Cursor, curl) + HTTP Streamable (claude.ai, Copilot, n8n)
Faits temporels avec périodes de validité
Chiffrement zero-knowledge AES-256-GCM côté client (memoraeu-mcp)
RGPD natif : endpoints export / suppression / historique intégrés
Fusion intelligente : détection et merge de mémoires similaires via LLM (Mistral/Ollama)

Démarrage rapide

☁️ Option A — Cloud géré (zéro config)

# Installer le client MCP
uvx memoraeu-mcp

# Ajouter dans votre config Claude Desktop :
# Server URL : https://api.memoraeu.com/mcp/sse
# Clé API sur : https://app.memoraeu.com

🏠 Option B — Auto-hébergement (gratuit, AGPL v3)

git clone https://github.com/pquattro/memoraeu-server
cd memoraeu-server
cp .env.example .env   # remplir MEMORAEU_SECRET, MEMORAEU_SALT, MISTRAL_API_KEY
docker compose up -d
# API disponible sur http://localhost:8000
# Docs : http://localhost:8000/docs
# Serveur MCP : http://localhost:8000/mcp/sse

Configuration

Toute la configuration se fait via variables d'environnement (voir .env.example)

Variable	Défaut	Description
`JWT_SECRET`	—	Requis. 32 caractères minimum.
`REGISTRATION_OPEN`	`true`	Autoriser les nouvelles inscriptions
`EMBED_PROVIDER`	`ollama`	`ollama` ou `mistral`
`EMBED_MODEL`	`nomic-embed-text`	Nom du modèle d'embedding
`EMBED_URL`	`http://localhost:11434`	URL de base Ollama
`MISTRAL_API_KEY`	—	Requis si `EMBED_PROVIDER=mistral`
`QDRANT_URL`	`http://qdrant:6333`	URL de l'instance Qdrant
`SQLITE_PATH`	`/data/memoraeu.db`	Chemin de la base SQLite

Connecter votre client MCP

Claude Desktop / Cursor / Windsurf (Legacy SSE)

{
  "mcpServers": {
    "memoraeu": {
      "url": "http://localhost:8000/mcp/sse",
      "headers": { "Authorization": "Bearer VOTRE_CLE_API" }
    }
  }
}

claude.ai (HTTP Streamable, nécessite une URL publique + OAuth) Voir la documentation

Mistral AI (connecteurs beta — La Plateforme)

connector = client.beta.connectors.create(
    name="memoraeu",
    server="https://api.memoraeu.com/mcp/sse?token=meu-sk-••••",
)

⚠️ Beta — discovery et SSE testés, exécution des tools en cours de déploiement par Mistral.

Pourquoi MemoraEU ?

	MemoraEU	Autres (ex: mem0)
Open source	✅ AGPL v3	✅ (core)
Hébergé en EU	✅ OVH France	❌ US
Zero-knowledge	✅ AES-256-GCM côté client	❌
Auto-hébergeable	✅ Docker Compose	✅
MCP natif	✅ stdio + SSE + HTTP Streamable	❌
Mistral connecteurs	✅ compatible (beta)
OAuth 2.0 PKCE	✅	❌
Graphe de connaissance temporel	✅	❌
Endpoints RGPD	✅ natifs	⚠️ partiel

Self-host vs Cloud

	Auto-hébergé	MemoraEU Cloud
Installation	Docker Compose	Inscription, c'est tout
Localisation des données	Votre serveur	EU (OVH, France)
Embeddings	Ollama (local)
Mises à jour	Manuelles	Automatiques
Prix	Gratuit (AGPL)

Architecture

Claude Desktop / Claude Code                 claude.ai · Cursor · Windsurf · ChatGPT
         │                                              │
         │ stdio (MCP)  memoraeu-mcp (uvx)
         ▼                                              │ OAuth 2.0 PKCE
  memoraeu_mcp/main.py                                 │
         │                                              ▼
         ├── Mistral API  ←── embeddings locaux   api/main.py  (FastAPI)
         │                    (avant chiffrement)
         │ HTTP + Bearer token                          ├── POST /mcp/sse   ← HTTP Streamable
         │ [contenu chiffré AES-256-GCM + vecteur]     ├── GET  /mcp/sse   ← SSE legacy
         ▼                                              ├── /oauth/*        ← PKCE
   api/main.py  (FastAPI)
         ├── Qdrant          ← recherche vectorielle
         ├── SQLite (memories)
         └── SQLite (facts)

Stack :

FastAPI
Qdrant — base vectorielle (Docker)
Mistral AI
MCP
SQLite — persistance des métadonnées
AES-256-GCM + PBKDF2-SHA256 (210k itérations)

Flux zero-knowledge

Variable	Rôle
`MEMORAEU_API_KEY`	Authentification HTTP — Bearer token envoyé à chaque requête
`MEMORAEU_SECRET`	Mot de passe — entrée PBKDF2 pour dériver la clé AES localement
`MEMORAEU_SALT`	Salt KDF unique par compte, généré à l'inscription
`MISTRAL_API_KEY`	Clé Mistral côté client — embeddings calculés avant chiffrement

remember()
  texte clair
    → PBKDF2(SECRET, SALT, 210k)
    → Mistral embed(texte clair)
    → AES-256-GCM(texte, clé)
    → POST /memories { blob chiffré, vecteur }  ← le serveur ne voit que l'opaque

Installer en package Python

pip install memoraeu

Avec les embeddings Mistral :

pip install "memoraeu[mistral]"

Conformité RGPD

Endpoint	Méthode	Description
`/gdpr/status`	`GET`	Statistiques des données stockées
`/gdpr/export`	`GET`	Export JSON complet (Art. 20)
`/gdpr/delete-account`	`DELETE`	Purge irréversible Qdrant + SQLite (Art. 17)
`/me/gdpr-history`	`GET`	Historique des opérations RGPD

Journal admin filtrable par organisation et date :

GET /gdpr/admin/log?org_id=...&date_from=YYYY-MM-DD
X-Admin-Key: <MEMORAEU_ADMIN_KEY>

Comment ça marche

Stocker une mémoire

Texte en clair
  → [LOCAL] Mistral compresse si > 300 caractères
  → [LOCAL] Mistral génère un vecteur d'embedding
  → [LOCAL] PBKDF2(SECRET, SALT, 210k itérations)
  → [LOCAL] AES-256-GCM(texte)
  → POST /memories { blob chiffré, vecteur }
  → [SERVEUR] similarité vectorielle → skip si > 94% doublon
  → [SERVEUR] SQLite ← métadonnées  |  Qdrant ← vecteur
  → Le serveur ne voit jamais le texte en clair.

Rappeler une mémoire

Requête texte (ex. "projet principal")
  → [LOCAL] Mistral génère le vecteur de la requête
  → POST /memories/search { vecteur, limit: 3 }
  → [SERVEUR] Qdrant cosine similarity → top-N blobs chiffrés
  → [LOCAL] AES-256-GCM déchiffre → texte en clair
  → Claude reçoit le contexte. Le serveur n'a vu qu'un vecteur.

Mémoire automatique (mode MCP stdio)

Le serveur MCP est conçu pour fonctionner sans intervention manuelle. Les descriptions des outils recall et remember instruisent Claude de les appeler automatiquement — recall au premier message de chaque session, remember dès qu'une information mérite d'être retenue. Au premier recall, le system prompt complet est injecté dans le contexte.

Contribuer

MemoraEU est open source (AGPL v3)

git clone https://github.com/pquattro/memoraeu-server
cd memoraeu-server
python -m venv .venv && source .venv/bin/activate
pip install -e .
cp .env.example .env  # configurer votre .env local
uvicorn api.main:app --reload

Gardez les PRs ciblées — une fonctionnalité ou un correctif par PR.

Domaines où l'aide est la plus utile : SDK JavaScript/TypeScript, app mobile, intégrations MCP supplémentaires, traductions.

Licence

AGPL v3 — Copyright (c)

Si vous faites tourner une version modifiée en tant que service réseau, vous devez rendre le code source disponible à vos utilisateurs.

English

MemoraEU gives your AI a persistent, encrypted memory — sovereign, zero-knowledge, hosted in Europe. Works with Claude, Cursor, Windsurf, ChatGPT, GitHub Copilot, n8n via MCP. Self-host for free (AGPL v3) or use the managed EU cloud

What it does

MemoraEU is a self-hostable memory server for AI assistants. It implements the Model Context Protocol (MCP) so any MCP-compatible client (Claude, Cursor, Windsurf, ChatGPT, GitHub Copilot, n8n…)

Semantic search powered by Qdrant + embeddings (Ollama or Mistral)
Multi-user / multi-org with JWT auth
MCP transports: Legacy SSE (Cursor, curl) + HTTP Streamable (claude.ai, Copilot, n8n)
Temporal facts with validity periods
Zero-knowledge encryption AES-256-GCM client-side (memoraeu-mcp)
Native GDPR: built-in export / deletion / history endpoints
Intelligent merge: similar memory detection and LLM-powered merge (Mistral/Ollama)

Quick start

☁️ Option A — Managed cloud (zero config)

# Install the MCP client
uvx memoraeu-mcp

# Add to your Claude Desktop config:
# Server URL: https://api.memoraeu.com/mcp/sse
# Get your API key at: https://app.memoraeu.com

🏠 Option B — Self-host (free, AGPL v3)

git clone https://github.com/pquattro/memoraeu-server
cd memoraeu-server
cp .env.example .env   # fill MEMORAEU_SECRET, MEMORAEU_SALT, MISTRAL_API_KEY
docker compose up -d
# API running at http://localhost:8000
# Docs: http://localhost:8000/docs
# MCP server: http://localhost:8000/mcp/sse

Configuration

All configuration is via environment variables (see .env.example)

Variable	Default	Description
`JWT_SECRET`	—	Required. Min 32 chars.
`REGISTRATION_OPEN`	`true`	Allow new user registration
`EMBED_PROVIDER`	`ollama`	`ollama` or `mistral`
`EMBED_MODEL`	`nomic-embed-text`	Embedding model name
`EMBED_URL`	`http://localhost:11434`	Ollama base URL
`MISTRAL_API_KEY`	—	Required if `EMBED_PROVIDER=mistral`
`QDRANT_URL`	`http://qdrant:6333`	Qdrant instance URL
`SQLITE_PATH`	`/data/memoraeu.db`	SQLite database path

Connect your MCP client

Claude Desktop / Cursor / Windsurf (Legacy SSE)

{
  "mcpServers": {
    "memoraeu": {
      "url": "http://localhost:8000/mcp/sse",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

claude.ai (HTTP Streamable, requires public URL + OAuth) See documentation

Mistral AI (beta connectors — La Plateforme)

connector = client.beta.connectors.create(
    name="memoraeu",
    server="https://api.memoraeu.com/mcp/sse?token=meu-sk-••••",
)

⚠️ Beta — discovery and SSE tested, tool execution being rolled out by Mistral.

Why MemoraEU?

	MemoraEU	Others (e.g. mem0)
Open source	✅ AGPL v3	✅ (core)
Hosted in EU	✅ OVH France	❌ US
Zero-knowledge	✅ AES-256-GCM client-side	❌
Self-hostable	✅ Docker Compose	✅
MCP native	✅ stdio + SSE + HTTP Streamable	❌
Mistral connectors	✅ compatible (beta)
OAuth 2.0 PKCE	✅	❌
Temporal knowledge graph	✅	❌
GDPR endpoints	✅ native	⚠️ partial

Self-host vs Cloud

	Self-hosted	MemoraEU Cloud
Setup	Docker Compose	Sign up, done
Data location	Your server	EU (OVH, France)
Embeddings	Ollama (local)
Updates	Manual	Automatic
Price	Free (AGPL)

Architecture

Claude Desktop / Claude Code                 claude.ai · Cursor · Windsurf · ChatGPT
         │                                              │
         │ stdio (MCP)  memoraeu-mcp (uvx)
         ▼                                              │ OAuth 2.0 PKCE
  memoraeu_mcp/main.py                                 │
         │                                              ▼
         ├── Mistral API  ←── local embeddings    api/main.py  (FastAPI)
         │                    (before encryption)
         │ HTTP + Bearer token                          ├── POST /mcp/sse   ← HTTP Streamable
         │ [AES-256-GCM ciphertext + vector]           ├── GET  /mcp/sse   ← SSE legacy
         ▼                                              ├── /oauth/*        ← PKCE
   api/main.py  (FastAPI)
         ├── Qdrant          ← vector search
         ├── SQLite (memories)
         └── SQLite (facts)

Stack:

FastAPI
Qdrant — vector database (Docker)
Mistral AI
MCP
SQLite — metadata persistence
AES-256-GCM + PBKDF2-SHA256 (210k iterations)

Zero-knowledge flow

Variable	Role
`MEMORAEU_API_KEY`	HTTP authentication — Bearer token sent with every request
`MEMORAEU_SECRET`	Password — PBKDF2 input to derive AES key locally
`MEMORAEU_SALT`	Per-account KDF salt, generated at registration
`MISTRAL_API_KEY`	Client-side Mistral key — embeddings computed before encryption

remember()
  plaintext
    → PBKDF2(SECRET, SALT, 210k)
    → Mistral embed(plaintext)
    → AES-256-GCM(plaintext, key)
    → POST /memories { ciphertext, vector }  ← server only sees opaque blobs

Install as Python package

pip install memoraeu

With Mistral embeddings:

pip install "memoraeu[mistral]"

GDPR compliance

Endpoint	Method	Description
`/gdpr/status`	`GET`	Stored data statistics
`/gdpr/export`	`GET`	Full JSON export (Art. 20)
`/gdpr/delete-account`	`DELETE`	Irreversible purge Qdrant + SQLite (Art. 17)
`/me/gdpr-history`	`GET`	GDPR operation history

Filterable admin log by organization and date:

GET /gdpr/admin/log?org_id=...&date_from=YYYY-MM-DD
X-Admin-Key: <MEMORAEU_ADMIN_KEY>

How it works

Storing a memory

Plaintext
  → [LOCAL] Mistral compresses if > 300 chars
  → [LOCAL] Mistral generates an embedding vector
  → [LOCAL] PBKDF2(SECRET, SALT, 210k iterations)
  → [LOCAL] AES-256-GCM(plaintext)
  → POST /memories { encrypted blob, vector }
  → [SERVER] vector similarity check → skip if > 94% duplicate
  → [SERVER] SQLite ← metadata  |  Qdrant ← vector
  → Server never sees plaintext. Ever.

Recalling a memory

Text query (e.g. "main project")
  → [LOCAL] Mistral generates query embedding
  → POST /memories/search { vector, limit: 3 }
  → [SERVER] Qdrant cosine similarity → top-N encrypted blobs
  → [LOCAL] AES-256-GCM decrypt → plaintext
  → Claude receives context. Server only ever saw a vector.

Auto-memory (MCP stdio mode)

The MCP server is designed to work without manual intervention. The recall and remember tool descriptions instruct Claude to call them automatically — recall on the first message of each session, remember whenever information is worth retaining. On the first recall call, the full behavior system prompt is injected into Claude's context.

Contributing

MemoraEU is open source (AGPL v3)

git clone https://github.com/pquattro/memoraeu-server
cd memoraeu-server
python -m venv .venv && source .venv/bin/activate
pip install -e .
cp .env.example .env  # configure your local .env
uvicorn api.main:app --reload

Please keep PRs focused — one feature or fix per PR.

Areas where help is most welcome: JavaScript/TypeScript SDK, mobile app, additional MCP client integrations, translations.

License

AGPL-3.0 — Copyright (C)

If you run a modified version as a network service, you must make the source available to your users.

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MemoraEu

MemoraEU Server

Français

Ce que ça fait

Démarrage rapide

☁️ Option A — Cloud géré (zéro config)

🏠 Option B — Auto-hébergement (gratuit, AGPL v3)

Configuration

Connecter votre client MCP

Pourquoi MemoraEU ?

Self-host vs Cloud

Architecture

Flux zero-knowledge

Installer en package Python

Conformité RGPD

Comment ça marche

Stocker une mémoire

Rappeler une mémoire

Mémoire automatique (mode MCP stdio)

Contribuer

Licence

English

What it does

Quick start

☁️ Option A — Managed cloud (zero config)

🏠 Option B — Self-host (free, AGPL v3)

Configuration

Connect your MCP client

Why MemoraEU?

Self-host vs Cloud

Architecture

Zero-knowledge flow

Install as Python package

GDPR compliance

How it works

Storing a memory

Recalling a memory

Auto-memory (MCP stdio mode)

Contributing

License

Related Servers

Alpha Vantage MCP Server

MCP Proxy Server

Jira Context MCP

OPNsense MCP Server

DICOM API

MCPBundles

mcp-memory-graph

Squidler.io

StatsWR MCP Server

ForeverVM

JSON MCP

NotebookLM Web Importer