Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Agent Memory MCP Server Remember that the user prefers dark mode"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Persistent memory for AI agents — store, retrieve and search knowledge across sessions. No more forgetting between conversations.
AI agents lose all context when a session ends. This MCP server gives agents a persistent knowledge store that survives across sessions, tools, and even different agent frameworks.
Related MCP server: haksnbot-memory
Store & Retrieve — Key-value storage with full persistence
Namespaces — Separate memories by project, user, or context
Tags — Categorize memories for easy filtering
Full-Text Search — Search across all stored knowledge
Access Tracking — See which memories are accessed most
Statistics — Dashboard showing memory usage
pip install agent-memory-mcp-server{
"mcpServers": {
"memory": {
"command": "uvx",
"args": ["agent-memory-mcp-server"]
}
}
}Tool | Description |
| Store a key-value pair persistently |
| Retrieve stored knowledge by key |
| Full-text search across all memories |
| List all memories in a namespace |
| Remove a memory |
| List all namespaces |
| Usage statistics |
"Remember that the user prefers dark mode"
"What do you know about Project Alpha?"
"Store this API response for later"
"What were the key decisions from last session?"Uses SQLite for zero-configuration persistent storage. Data is stored locally — no cloud, no API keys, no costs. The database file (memory.db) is created automatically in the server directory.
Category | Servers |
đź”— Blockchain | |
🌍 Data | Weather · Germany · Agriculture · Space · Aviation · EU Companies |
đź”’ Security | |
🤖 Agent Infra | Memory · Directory · Hub · Reputation |
🔬 Research | Academic · LLM Benchmark · Legal |
→ Full catalog (40+ servers)
MIT
Ein Memory löschen.
Args: key: Schlüssel des zu löschenden Eintrags namespace: Namespace (Standard: "default")
Inputs: key (required), namespace.
Alle Memories auflisten.
Args: namespace: Optional — nur diesen Namespace zeigen limit: Maximale Anzahl (Standard: 20)
Inputs: namespace, limit.
Alle Namespaces mit Anzahl Memories auflisten.
Zeigt eine Ăśbersicht aller verwendeten Namespaces.
Inputs: no named parameters.
Gespeichertes Wissen abrufen.
Args: key: SchlĂĽssel des gesuchten Eintrags namespace: Namespace (Standard: "default")
Inputs: key (required), namespace.
Memories durchsuchen.
Sucht in Keys und Values nach dem Suchbegriff. Optional filterbar nach Namespace und Tags.
Args: query: Suchbegriff namespace: Optional — nur in diesem Namespace suchen tags: Optional — nur Memories mit diesen Tags limit: Maximale Ergebnisse (Standard: 10)
Inputs: query (required), namespace, tags, limit.
Speicher-Statistiken abrufen.
Zeigt: Gesamtzahl Memories, Namespaces, meistgenutzte und zuletzt aktualisierte Einträge.
Inputs: no named parameters.
Wissen persistent speichern.
Speichert einen Key-Value-Eintrag der über Sessions hinweg erhalten bleibt. Ideal für Fakten, Präferenzen, Kontext.
Args: key: Eindeutiger SchlĂĽssel (z.B. "user_preference_language") value: Der zu speichernde Inhalt (Text, JSON, etc.) namespace: Namespace zur Trennung (z.B. "project_x", "user_123") tags: Optionale Tags zum Kategorisieren (z.B. ["preference", "important"])
Inputs: key (required), value (required), namespace, tags.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
Scored across 7 tools
Each tool has a clearly distinct purpose: store, retrieve, list, search, delete, list namespaces, and stats. No overlap or ambiguity.
Tools follow a consistent 'memory_' prefix with verbs except for 'memory_namespaces' and 'memory_stats', which use nouns. Minor deviation from the verb_noun pattern.
Seven tools are appropriate for a memory management server, covering essential operations without being too few or too many.
Covers all basic memory operations (create, read, list, search, delete, stats, namespace listing), but lacks an explicit update operation, though store can overwrite existing keys.
Persistent cloud memory for AI agents. Store and search key-value memories across sessions.
Persistent memory for AI agents. Search and store durable facts, preferences and decisions.
Persistent memory for AI agents. Search, store, and recall across sessions.
Persistent memory for AI agents: save, search and connect context across tools and sessions.
