openmemory
Persistent long-term agent memory for storing and querying past work, patterns, and learnings.
Installation
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
Voir la source ↗GuidesInstructions
OpenMemory (Persistent Agent Memory)
You have access to OpenMemory for persistent long-term memory across sessions.
Memory Tools
| Tool | Purpose |
|---|---|
openmemory_query |
Semantic search across memories by similarity |
openmemory_store |
Store new memories with sector classification |
openmemory_list |
List recent memories for a user/agent |
openmemory_get |
Retrieve specific memory by ID |
openmemory_reinforce |
Boost salience of important memories |
Memory Sectors
Memories are classified into sectors:
| Sector | Use Case | Example |
|---|---|---|
| episodic | Events, task history | "Implemented auth flow for project X" |
| semantic | Facts, learned patterns | "Always add Context7 lookup before Rust implementation" |
| procedural | How-to knowledge | "Steps to deploy with ArgoCD" |
Usage Patterns
Before starting a task:
openmemory_query({ query: "similar implementations", sector: "episodic" })
After completing a task:
openmemory_store({
content: "Implemented OAuth2 with PKCE for React app using Effect",
sector: "episodic",
tags: ["auth", "react", "effect"]
})
For important learnings:
openmemory_reinforce({ memory_id: "mem_xyz", boost: 1.5 })
Best Practices
- Query before implementing - Check for similar past work
- Store after completing - Save successful patterns and solutions
- Reinforce important memories - Boost salience of critical learnings
- Tag memories well - Include relevant technologies and patterns
Exemples
Consultez les exemples du dépôt source.
Voir la source ↗Historique source
- Date d’indexation
- 2026-01-20
- Mise à jour de l’index
- 2026-03-04
- Branch
- main
Les dates concernent ce répertoire. Consultez le dépôt pour l’historique du code.
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