AI Skill Hub 强烈推荐:Memori智能体记忆系统 是一款优质的AI工具。在 GitHub 上收获超过 14.7k 颗 Star,AI 综合评分 8.2 分,在同类工具中表现稳健。如果你正在寻找可靠的AI工具解决方案,这是一个值得深入了解的选择。
Memori智能体记忆系统 是一款基于 Python 开发的开源工具,专注于 智能体内存、MCP协议、记忆管理 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
Memori智能体记忆系统 是一款基于 Python 开发的开源工具,专注于 智能体内存、MCP协议、记忆管理 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:pip 安装(推荐)
pip install memori
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install memori
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/MemoriLabs/Memori
cd Memori
pip install -e .
# 验证安装
python -c "import memori; print('安装成功')"
# 命令行使用
memori --help
# 基本用法
memori input_file -o output_file
# Python 代码中调用
import memori
# 示例
result = memori.process("input")
print(result)
# memori 配置文件示例(config.yml) app: name: "memori" debug: false log_level: "INFO" # 运行时指定配置文件 memori --config config.yml # 或通过环境变量配置 export MEMORI_API_KEY="your-key" export MEMORI_OUTPUT_DIR="./output"
<p align="center"> <strong>Memory from what agents do, not just what they say.</strong> </p>
<p align="center"> <i>Memori plugs into the software and infrastructure you already use. It is LLM, datastore and framework agnostic and seamlessly integrates into the architecture you've already designed.</i> </p>
<p align="center"> <strong>→ <a href="https://memorilabs.ai/docs/memori-cloud/">Memori Cloud</a></strong> — Zero config. Get an API key and start building in minutes. </p> <p align="center"> <a href="https://trendshift.io/repositories/15435" target="_blank"><img src="https://trendshift.io/api/badge/repositories/15435" alt="MemoriLabs%2FMemori | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a> </p>
<p align="center"> <a href="https://badge.fury.io/py/memori"> <img src="https://badge.fury.io/py/memori.svg" alt="PyPI version"> </a> <a href="https://www.npmjs.com/package/@memorilabs/memori"> <img src="https://img.shields.io/npm/v/@memorilabs/memori.svg" alt="NPM version"> </a> <a href="https://pepy.tech/projects/memori"> <img src="https://static.pepy.tech/badge/memori" alt="Downloads"> </a> <a href="https://opensource.org/license/apache-2-0"> <img src="https://img.shields.io/badge/license-Apache%202.0-blue" alt="License"> </a> <a href="https://discord.gg/abD4eGym6v"> <img src="https://img.shields.io/discord/1042405378304004156?logo=discord" alt="Discord"> </a> </p>
<p align="center"> <a href="https://github.com/MemoriLabs/Memori/stargazers"> <img src="https://img.shields.io/badge/⭐%20Give%20a%20Star-Support%20the%20project-orange?style=for-the-badge" alt="Give a Star"> </a> </p>
<p align="center"> <strong>Choose memory that performs</strong> </p>
---
client = OpenAI() mem = Memori().llm.register(client)
mem.attribution(entity_id="user_123", process_id="support_agent")
response = client.chat.completions.create( model="gpt-4o-mini", messages=[{"role": "user", "content": "My favorite color is blue."}] )
python -m memori ```
This will display a menu of the available options. For more information about what you can do with the Memori CLI, please reference Command Line Interface.
<details open> <summary><b>TypeScript SDK</b></summary>
npm install @memorilabs/memori </details>
<details open> <summary><b>Python SDK</b></summary>
pip install memori </details>
python -m memori sign-up <email_address>
Memori Advanced Augmentation is always free for developers!
Once you've obtained an API key, set the following environment variable (used by both Python and TypeScript SDKs):
bash export MEMORI_API_KEY=[api_key] ```
The Memori CLI uses your exported environment first, then fills missing values from a .env file in the directory where you run the command.
Sign up at app.memorilabs.ai, get a Memori API key, and start building. Full docs: memorilabs.ai/docs/memori-cloud/.
Set MEMORI_API_KEY and your LLM API key (e.g. OPENAI_API_KEY), then:
<details open> <summary><b>TypeScript SDK</b></summary>
import { OpenAI } from 'openai';
import { Memori } from '@memorilabs/memori';
// Requires MEMORI_API_KEY and OPENAI_API_KEY in your environment
const client = new OpenAI();
const mem = new Memori().llm
.register(client)
.attribution('user_123', 'support_agent');
async function main() {
await client.chat.completions.create({
model: 'gpt-4o-mini',
messages: [{ role: 'user', content: 'My favorite color is blue.' }],
});
// Conversations are persisted and recalled automatically in the background.
const response = await client.chat.completions.create({
model: 'gpt-4o-mini',
messages: [{ role: 'user', content: "What's my favorite color?" }],
});
// Memori recalls that your favorite color is blue.
} </details>
<details open> <summary><b>Python SDK</b></summary>
```python from memori import Memori from openai import OpenAI
For more examples and demos, check out the Memori Cookbook.
The Memori CLI is the unified tool for managing your account, keys, and quotas across all SDKs. To use it, execute the following from the command line:
```bash
创新的Agent记忆基础设施方案,填补MCP生态记忆层空白。架构优雅、扩展性强,社区活跃度高,是构建智能体系统的关键组件。
该工具使用 NOASSERTION 协议,商用场景请仔细阅读协议条款,必要时咨询法律意见。
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。
📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。
总体来看,Memori智能体记忆系统 是一款质量优秀的AI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 | Memori |
| 原始描述 | 开源MCP工具:Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns ag。⭐14.7k · Python |
| Topics | 智能体内存MCP协议记忆管理多轮对话Agent框架 |
| GitHub | https://github.com/MemoriLabs/Memori |
| License | NOASSERTION |
| 语言 | Python |
收录时间:2026-05-20 · 更新时间:2026-05-30 · License:NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。