Hermes Memory MCP
Click on "Deploy 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., "@Hermes Memory MCPlist draft skills"
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.
🧠 Hermes Memory MCP
本地增强型记忆系统 + 自我进化能力 · v2.3
基于 Model Context Protocol (MCP) 的本地记忆系统,5 个版本演进到 v2.3 自我进化阶段:从被动存储 → 主动学习 → 智能检索 → 自我进化。
✨ v2.3 三大自进化能力
能力 | 说明 | MCP Tools |
Skill 自动创建 | 从对话上下文抽取 SKILL.md 草稿 → 审核 → 一键部署到 Trae |
|
周期性 nudge 调度 | 6 个内置后台任务自动维护记忆库(清理/压缩/反思/晋升/健康检查) |
|
Trajectory 训练管道 | 自动捕获所有 MCP Tool 调用 → 导出 JSONL → 用于 RLHF/DPO 微调 |
|
Related MCP server: spatial-memory-mcp
📊 项目指标
维度 | 数据 |
端到端测试 | 51 / 51 通过(v2.1=23 + v2.2=11 + v2.3=17) |
MCP Tool 总数 | 31(v2.1=15 + v2.2=7 + v2.3=9) |
Skill 数 | 5(memory / evolution / knowledge / reflection / auto-orchestrator) |
6 个 nudge |
|
数据 Schema | 20 张表(兼容升级 v2.1 老数据) |
🏗️ 架构
hermes-mcp/
├── hermes_memory_mcp/ # MCP Server 核心
│ ├── server.py # 31 个 @mcp.tool() 入口
│ ├── core/ # MemoryManager(5 版本核心)
│ ├── storage/ # SQLite + ChromaDB
│ ├── orchestrator/ # v2.2 + v2.3 新增
│ │ ├── multisignal.py # v2.2 多信号融合
│ │ ├── system_prompt.py # v2.2 三层 Prompt
│ │ ├── pre_compress.py # v2.2 压缩前捕获
│ │ ├── skill_factory.py # v2.3 Skill 自动创建
│ │ ├── scheduler.py # v2.3 nudge 调度
│ │ ├── trajectory.py # v2.3 Trajectory 训练管道
│ │ └── nudges/ # v2.3 6 个后台任务
│ └── utils/ # audit / sanitizer / embedder
├── skills/ # 5 个 Trae Skill
│ └── hermes-{memory,evolution,knowledge,reflection,auto-orchestrator}/
├── tests/ # e2e + 报告 + 复盘 + 打包
│ ├── test_e2e.py # v2.1 基础(23 用例)
│ ├── test_v22.py # v2.2 多信号 + prompt(11 用例)
│ ├── test_v23.py # v2.3 自进化(17 用例)
│ ├── deployment_report.md # 部署报告(v2.1 → v2.2 → v2.3)
│ ├── RETROSPECTIVE_v23.md # v2.3 完整复盘
│ └── build_v23_bundle.py # 打包脚本
├── .trae/
│ ├── mcp.json # Trae MCP 配置
│ └── specs/ # 7 个 spec 文档
│ ├── debug-and-deploy-hermes-mcp/
│ ├── enhance-hermes-memory-mcp/
│ ├── reference-hermes-agent-online/
│ ├── trae-auto-memory/
│ ├── v22-evolution/
│ ├── v23-self-evolution/
│ ├── v23-retrospective-bundle/
│ └── github-publish-v23/
└── hermes_memory_mcp_server.py # 入口脚本🚀 快速开始
# 1. 安装依赖
pip install mcp chromadb sentence-transformers networkx jieba pyyaml aiofiles
# 2. 配置 Trae MCP(.trae/mcp.json 已就绪)
# command: C:/Python314/python.exe
# args: e:/hermes-project/hermes-mcp/hermes_memory_mcp_server.py
# 3. 启动(默认离线 Mock Embedder;设 HERMES_USE_REAL_EMBED=1 用真实模型)
python hermes_memory_mcp_server.py
# 4. 跑端到端测试
python tests/test_e2e.py # 23/23
python tests/test_v22.py # 11/11
python tests/test_v23.py # 17/17
# 5. 打包 v23 交付物
python tests/build_v23_bundle.py🧬 5 大版本演进
版本 | 阶段 | 关键能力 | 状态 |
v2.0 | 基础 | retain/recall/reflect/evolve | ✅ 17 e2e |
v2.1 | 自动化 | auto_retain/startup_recall/summarize_session | ✅ 23 e2e |
v2.2 | 智能化 | 多信号检索 / 三层 prompt / on_pre_compress / Linked / self-healing | ✅ 34 e2e |
v2.3 | 自我进化 | Skill 自动创建 / 6 nudge / Trajectory 训练管道 | ✅ 51 e2e |
📐 业界借鉴
NousResearch/hermes-agent → 三层 System Prompt(v2.2)
Letta → on_pre_compress + 反思代理独立化(v2.2 / v2.3)
Mem0 → 多信号融合 + Linked Memory(v2.2)
📝 复盘与部署
打包产物:
tests/v23_bundle_*.zip(48.5KB / 16 文件)
📜 License
Private · 仅供 owner=wcy88 内部使用
This server cannot be deployed
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