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Ajouter une mémoire multimodale permanente aux agents MCP et Py…

Utilisez SimpleMem pour stocker, compresser, indexer et récupérer des souvenirs textuels ou multimodaux pour des agents via des intégrations MCP ou Python.

Qu'est-ce que Ajouter une mémoire multimodale permanente aux agents MCP et Py… ?

SimpleMem est une bibliothèque et un serveur MCP conçus pour doter les agents d'une mémoire persistante et multimodale. Ce skill permet aux agents de stocker des souvenirs textuels ou visuels, de les compresser pour économiser de l'espace, de les indexer pour une recherche rapide et de les retrouver sur demande, le tout via un serveur MCP (pour les agents compatibles MCP comme Claude Code) ou une intégration Python directe (pour les frameworks d'agents Python). Il est utile pour créer des agents dotés d'une mémoire à long terme, capables de se souvenir d'interactions passées, de documents, d'images ou d'autres données multimodales, améliorant ainsi leur continuité contextuelle et leur personnalisation. SimpleMem repose sur des modèles et embeddings configurés pour le backend choisi, et son package est disponible sur PyPI. Ce skill est particulièrement adapté aux développeurs d'agents IA qui souhaitent implémenter une mémoire non volatile et riche sur différentes plateformes.

Compatible avec~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/add-multimodal-lifelong-memory-to-mcp-and-python-agents-with-simplemem

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Ajouter une mémoire multimodale permanente aux agents MCP et Python avec SimpleMem

Utilisez SimpleMem pour stocker, compresser, indexer et récupérer des souvenirs textuels ou multimodaux pour des agents via des intégrations MCP ou Python.

Prérequis

Package Python SimpleMem ou serveur MCP, client compatible MCP ou environnement d'exécution d'agent Python, données sources de mémoire, dépendances de modèle/embedding configurées pour le backend choisi.

Installation

Utilisez le chemin d'installation en amont ou la configuration adaptée à votre environnement :

  • git clone https://github.com/aiming-lab/SimpleMem.git
  • pip install -r requirements.txt
  • pip install -e . # par défaut : texte + multimodal + evolver
  • pip install -e ".[server]" # + serveur MCP / HTTP (mcp, fastapi, ...)

Exigences et remarques de la source amont :

  • python

Notes d'utilisation de base ou de démarrage :

Documentation

Source

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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act Local GitHub Actions Runner

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Add a browser review checkpoint before risky agent actions with

Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

Add managed long-term memory to LangGraph agents with LangMem

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Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

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Calls Adobe Firefly

Adobe Photoshop API Batch Processor

Automates image editing workflows via the Adobe Photoshop API (Firefly Services). Supports smart object replacement, action playback, and PSD layer manipulation at scale.

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