Easy Memory MCP Server
@FlippySun
基本信息
关于 Easy Memory MCP Server
Easy Memory MCP - Dual-engine embedding service with Qdrant vector store
Easy Memory MCP Server 配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"easy-memory": {
"command": "npx",
"args": [
"-y",
"easy-memory@latest"
],
"env": {
"EASY_MEMORY_URL": "https://memory.zhiz.chat/mcp",
"EASY_MEMORY_TOKEN": "<YOUR-TOKEN Get By: https://memory.zhiz.chat/>"
}
}
}
}Easy Memory MCP Server 工具
工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
概览
What is Easy Memory?
Easy Memory is an MCP (Model Context Protocol) memory service that persists AI memory across sessions and projects. It integrates with Qdrant vector database and embedding models (official OpenAI via compatible relay or Ollama), and provides dual-shell architecture: MCP Shell (stdio) for direct communication with AI clients like Claude Desktop, Cursor, and VS Code, and HTTP Shell (RESTful API) for remote access and multi-client sharing. It is intended for developers who want their AI assistants to retain context and knowledge between conversations.
How to use Easy Memory?
Easy Memory can be run via npx easy-memory, Docker Compose, or from source. Configure it by setting environment variables such as QDRANT_URL, QDRANT_API_KEY, and OLLAMA_BASE_URL for local setups, or EASY_MEMORY_URL and EASY_MEMORY_TOKEN for remote proxy mode. For client integration, edit the MCP configuration file (e.g., claude_desktop_config.json, .vscode/mcp.json) with the appropriate command and environment variables.
Key features of Easy Memory
- Dual shell architecture: MCP (stdio) and HTTP (RESTful API)
- Remote proxy mode – no local Qdrant or Ollama required
- Supports multiple AI clients: Claude Desktop, Cursor, VS Code
- Persistent memory across sessions and projects
- Semantic search with hybrid retrieval (vector + BM25)
- 8 MCP tools: save, search, forget, status (with aliases)
Use cases of Easy Memory
- Enable AI assistants to remember facts across conversations and projects
- Share a central memory store among multiple clients via HTTP API
- Run a remote memory
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