
Memory
@modelcontextprotocol
Memory について
Model Context Protocol Servers
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"memory": {
"command": "docker",
"args": [
"run",
"-i",
"-v",
"claude-memory:/app/dist",
"--rm",
"mcp/memory"
]
}
}
}ツール
9Create multiple new entities in the knowledge graph
Create multiple new relations between entities
Add new observations to existing entities
Remove entities and their relations
Remove specific observations from entities
Remove specific relations from the graph
Read the entire knowledge graph
Search for nodes based on query
Retrieve specific nodes by name
概要
What is Memory?
Memory is an MCP server that provides persistent memory using a local knowledge graph. It lets AI assistants like Claude remember information about the user across chats by storing entities, relations, and observations.
How to use Memory?
Configure Memory in your MCP client (Claude Desktop or VS Code) using Docker or npx. Optionally set the MEMORY_FILE_PATH environment variable to customize the storage file. Use the provided tools (e.g., create_entities, create_relations, add_observations) and the knowledge-graph resource to read and modify the graph.
Key features of Memory
- Persistent memory via local knowledge graph
- Entities with types and atomic observations
- Directed relations in active voice
- CRUD tools for graph manipulation
- Readable knowledge graph resource with live updates
- Configurable JSONL file storage
Use cases of Memory
- Remembering user identity and preferences across sessions
- Storing recurring behaviors, habits, and interests
- Tracking personal and professional goals
- Maintaining relationship networks for context
- Customizing assistant responses with past information
FAQ from Memory
How does Memory persist data?
Data is saved to a local JSONL file. The default path is memory.jsonl in the server directory, but can be overridden with the MEMORY_FILE_PATH environment variable.
What tools does Memory provide?
Memory offers create_entities, create_relations, add_observations, delete_entities, delete_observations, delete_relations, read_graph, search_nodes, and open_nodes. All tools are designed for a knowledge graph.
What runtime is needed?
Memory can be run via Docker or using Node.js with npx. No external database is required.
How do I configure the storage file path?
Set the MEMORY_FILE_PATH environment variable in the MCP server configuration (e.g., in claude_desktop_config.json). The default location is memory.jsonl in the server directory.
Does Memory support VS Code?
Yes. Memory can be installed in VS Code using the provided one‑click buttons or by adding the configuration to the user or workspace MCP settings file.
「メモリとナレッジ」の他のコンテンツ
Memory Bank MCP Server
alioshrA Model Context Protocol (MCP) server implementation for remote memory bank management, inspired by Cline Memory Bank.
Jupyter Notebook MCP Server (for Cursor)
jbenoModel Context Protocol (MCP) server designed to allow AI agents within Cursor to interact with Jupyter Notebook (.ipynb) files
Basic Memory
basicmachines-coAI conversations that actually remember. Never re-explain your project to your AI again. Join our Discord: https://discord.gg/tyvKNccgqN
MCP server for Obsidian
MarkusPfundsteinMCP server that interacts with Obsidian via the Obsidian rest API community plugin
MemoryMesh
CheMiguel23A knowledge graph server that uses the Model Context Protocol (MCP) to provide structured memory persistence for AI models.
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