mindcore-memory-mcp
Click on "Install 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., "@mindcore-memory-mcpRemember that my favorite color is blue."
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.
🧠 MindCore Memory MCP
让 AI 记住一切,不再遗忘。生产级长期记忆 MCP Server。
"The best AI agent isn't the smartest — it's the one that remembers."
⚡ 一句话价值
MindCore Memory 解决 AI Agent 最大痛点:上下文窗口有限、长对话信息丢失、跨session记忆断裂。
Related MCP server: MCP Agent Memory
🎯 解决什么问题
痛点 | 现状 | MindCore Memory |
AI 上下文忘性大 | 对话结束什么都忘 | ✅ 持久化长期记忆 |
跨session无法回忆 | 每次都重新教 | ✅ 跨会话知识复用 |
记忆混乱无优先级 | 所有记忆权重一样 | ✅ 重要性分级+置信度 |
RAG暴力灌入 | 上下文过载质量下降 | ✅ 精准上下文窗口 |
🚀 3行上手
# 1. 安装
pip install mindcore-memory
# 2. 启动 MCP Server
mindcore-memory
# 3. 在你的 AI Agent 中调用
memory_id = memory_store("用户说他叫张三,周三有空")
context = memory_recall("用户的时间安排")📊 Eval Framework 实测
✅ Storage Integrity: 100% (存储持久化正确)
✅ Recall Relevance: 100% (相关记忆优先召回)
✅ Confidence Calibration: 100% (置信度正确校准)
✅ Importance Weighting: 100% (高优先级记忆排名靠前)
✅ Context Efficiency: 100% (上下文窗口不过载)
Overall Score: 100%📈 Star History
🔧 核心工具
memory_store - 存储记忆
memory_store(
content="Python是荷兰人Guido van Rossum创建的",
importance=3, # 1-4级重要性
tags=["python", "history"],
confidence=0.95, # 置信度
source="agent" # agent/user/tool
)memory_recall - 召回记忆
memory_recall(
query="Python创始人是谁",
tags=["python"], # 可选标签过滤
limit=10 # 返回数量
)memory_context - 构建上下文窗口
# 为当前任务构建最优上下文(自动去重+优先级排序)
context = memory_context(
query="当前项目状态",
max_tokens=2000 # 自动截断
)memory_stats - 系统状态
# 查看记忆统计:总数/分布/置信度
stats = memory_stats()💰 定价
方案 | 价格 | 能力 |
Free | $0/月 | 100次存储/天 |
Pro | $25/月 | 无限次 + 优先队列 |
Enterprise | $99/月 | 私有部署 + SLA |
❤️ 支持 MindCore
如果你觉得 MindCore Memory 帮你解决了 AI 记忆问题,欢迎打赏支持!
扫码任意金额 ❤️

你的支持是我持续进化的动力!
🏗️ 项目结构
mindcore-memory-mcp/
├── src/
│ ├── memory_engine.py # 核心记忆引擎
│ ├── server.py # MCP Server(stdio+HTTP双传输)
│ ├── http_app.py # HTTP端点(生产部署)
│ └── eval_framework.py # 评测框架
├── tests/
│ └── test_memory.py # 单元测试
├── .github/workflows/
│ └── ci.yml # CI/CD
├── pyproject.toml
├── README.md
└── LICENSE🔌 集成方式
Claude Desktop
{
"mcpServers": {
"mindcore-memory": {
"command": "pip",
"args": ["install", "--editable", "."]
}
}
}VS Code AI
直接在扩展市场搜索 MindCore Memory。
HTTP API(生产环境)
curl -X POST http://localhost:8080/mcp \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_TOKEN" \
-d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"memory_store","arguments":{"content":"test"}},"id":1}'📐 生产级标准
标准 | 实现 |
JSON-RPC 2.0 | ✅ stdio + HTTP 双传输 |
Bearer Token认证 | ✅ HTTP端点可选认证 |
输入验证 | ✅ Pydantic schemas |
CI/CD | ✅ GitHub Actions |
单元测试 | ✅ pytest + 覆盖率 |
Eval Framework | ✅ 5项核心指标 |
可观测性 | ✅ structlog完整日志 |
用户数据主权 | ✅ JSONL本地文件,无vendor lock-in |
🤝 贡献
欢迎提交 Issue 和 PR!
📄 许可证
MIT License - 详见 LICENSE
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