AI Skill Hub 推荐使用:智能记忆 是一款优质的MCP工具。AI 综合评分 7.5 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
智能记忆 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
智能记忆 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/varun29ankuS/shodh-memory
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"----": {
"command": "npx",
"args": ["-y", "shodh-memory"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 智能记忆 执行以下任务... Claude: [自动调用 智能记忆 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"____": {
"command": "npx",
"args": ["-y", "shodh-memory"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
<p align="center"> <img src="https://raw.githubusercontent.com/varun29ankuS/shodh-memory/main/assets/logo.png" width="120" alt="Shodh-Memory"> </p>
<p align="center"><b>Persistent cognitive memory for AI agents and robots. Remembers what matters, forgets what doesn't, gets smarter with use.</b></p>
<p align="center"> <a href="https://github.com/varun29ankuS/shodh-memory/actions"><img src="https://github.com/varun29ankuS/shodh-memory/workflows/CI/badge.svg" alt="build"></a> <a href="https://registry.modelcontextprotocol.io/v0/servers?search=shodh"><img src="https://img.shields.io/badge/MCP-Registry-green" alt="MCP Registry"></a> <a href="https://cursor.directory/plugins/shodh-memory-1"><img src="https://img.shields.io/badge/Cursor-Directory-black?logo=cursor" alt="Cursor Directory"></a> <a href="https://crates.io/crates/shodh-memory"><img src="https://img.shields.io/crates/v/shodh-memory.svg" alt="crates.io"></a> <a href="https://www.npmjs.com/package/@shodh/memory-mcp"><img src="https://img.shields.io/npm/v/@shodh/memory-mcp.svg?logo=npm" alt="npm"></a> <a href="https://pypi.org/project/shodh-memory/"><img src="https://img.shields.io/pypi/v/shodh-memory.svg" alt="PyPI"></a> <a href="https://hub.docker.com/r/varunshodh/shodh-memory"><img src="https://img.shields.io/docker/pulls/varunshodh/shodh-memory.svg?logo=docker" alt="Docker"></a> <a href="#robotics--ros2"><img src="https://img.shields.io/badge/Zenoh%20%2F%20ROS2-ready-orange" alt="Zenoh/ROS2"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/license-Apache%202.0-blue.svg" alt="License"></a> <a href="https://discord.gg/HrpzXqTtEp"><img src="https://img.shields.io/discord/1471830549818642432?logo=discord&label=Discord&color=5865F2" alt="Discord"></a> </p>
---
<p align="center"> <img src="https://raw.githubusercontent.com/varun29ankuS/shodh-memory/main/assets/Shodh_preview.gif" width="800" alt="Shodh-Memory Demo — Claude Code with persistent memory and TUI dashboard"> </p>
AI agents forget everything between sessions. Robots lose context between missions. They repeat mistakes, miss patterns, and treat every interaction like the first one.
Shodh-Memory fixes this. It's persistent memory that actually learns — memories you use often become easier to find, old irrelevant context fades automatically, and recalling one thing brings back related things. Works for chat agents (MCP/HTTP), robots (Zenoh/ROS2), and edge devices. No API keys. No cloud. No external databases. One binary.
shodh init # First-time setup — creates config, generates API key, downloads AI model shodh server # Start the memory server on :3030 shodh setup-hooks # Print instructions to set up Claude Code hooks shodh tui # Launch the TUI dashboard shodh status # Check server health shodh doctor # Diagnose issues ```
One binary, all functionality. No Docker, no API keys, no external dependencies.
docker run -d -p 3030:3030 -v shodh-data:/data varunshodh/shodh-memory
SHODH_ZENOH_ENABLED=true SHODH_ZENOH_LISTEN=tcp/0.0.0.0:7447 shodh server
<details> <summary>Environment variables</summary>
SHODH_ENV=production # Production mode
SHODH_API_KEYS=key1,key2,key3 # Comma-separated API keys
SHODH_HOST=127.0.0.1 # Bind address (default: localhost)
SHODH_PORT=3030 # Port (default: 3030)
SHODH_MEMORY_PATH=/var/lib/shodh # Data directory
SHODH_REQUEST_TIMEOUT=60 # Request timeout in seconds
SHODH_MAX_CONCURRENT=200 # Max concurrent requests
SHODH_CORS_ORIGINS=https://app.example.com </details>
<details> <summary>Docker Compose with TLS</summary>
services:
shodh-memory:
image: varunshodh/shodh-memory:latest
environment:
- SHODH_ENV=production
- SHODH_HOST=0.0.0.0
- SHODH_API_KEYS=${SHODH_API_KEYS}
volumes:
- shodh-data:/data
networks:
- internal
caddy:
image: caddy:latest
ports:
- "443:443"
volumes:
- ./Caddyfile:/etc/caddy/Caddyfile
networks:
- internal
volumes:
shodh-data:
networks:
internal: </details>
<details> <summary>Reverse proxy (Nginx / Caddy)</summary>
The server binds to 127.0.0.1 by default. For network deployments, place behind a reverse proxy:
memory.example.com {
reverse_proxy localhost:3030
} </details>
npx @shodh/memory-mcp setup-hooks
Step 1 gives Claude persistent memory tools. Step 2 installs [Claude Code hooks](https://docs.anthropic.com/en/docs/claude-code/hooks) that automatically capture context from every session — memories surface without you having to ask.
<details>
<summary>Or with Docker (for production / shared servers)</summary>
bash
160+ endpoints on http://localhost:3030. All /api/* endpoints require X-API-Key header.
<details> <summary>Quick examples</summary>
```bash
[1] Cowan, N. (2010). The Magical Mystery Four. Current Directions in Psychological Science. [2] Magee & Grienberger (2020). Synaptic Plasticity Forms and Functions. Annual Review of Neuroscience. [3] Subramanya et al. (2019). DiskANN. NeurIPS 2019.
高质量的AI智能体记忆工具
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
总体来看,智能记忆 是一款质量良好的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | shodh-memory |
| 原始描述 | 开源MCP工具:Cognitive memory for AI agents — learns from use, forgets what's irrelevant, str。⭐215 · Rust |
| Topics | ai-agentsai-memoryrust |
| GitHub | https://github.com/varun29ankuS/shodh-memory |
| License | Apache-2.0 |
| 语言 | Rust |
收录时间:2026-05-29 · 更新时间:2026-05-30 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端