AI Skill Hub 强烈推荐:Kleos 是一款优质的MCP工具。AI 综合评分 8.0 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。
Kleos 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。
Kleos 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/Ghost-Frame/Kleos
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"kleos": {
"command": "npx",
"args": ["-y", "kleos"]
}
}
}
# 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 Kleos 执行以下任务... Claude: [自动调用 Kleos 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": {
"kleos": {
"command": "npx",
"args": ["-y", "kleos"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
<img src="docs/assets/banner.svg" width="800" alt="Kleos Banner" />
./kleos-install
./kleos-install-gui
On Windows, install with the PowerShell script (it fetches the windows-x64 binaries from the latest release):
powershell irm https://raw.githubusercontent.com/Ghost-Frame/Kleos/main/dist/install.ps1 | iex
Other platforms build from source (below).
The installer walks you through component selection, server configuration, embedding provider setup, security key generation, and optional systemd/launchd service registration. Choose a profile (Server, Agent Host, Full, Custom) or pick individual components.
**Or build from source:**
bash git clone https://github.com/Ghost-Frame/Kleos.git && cd Kleos
sudo apt install protobuf-compiler libpcsclite-dev
cargo build --release -p kleos-server -p kleos-cli KLEOS_BOOTSTRAP_SECRET=pick-a-secret \ KLEOS_SESSION_KEY=$(openssl rand -hex 32) \ ./target/release/kleos-server
`KLEOS_SESSION_KEY` is a 32-byte hex HMAC key for session tokens. Leave it
unset for a quick local try and the server generates an ephemeral one at
startup (with a warning) -- fine for one run, but sessions won't survive a
restart. Set it explicitly for anything you plan to keep running.
Server starts on `127.0.0.1:4200`. In another terminal:
**First run:** with default features, the server background-downloads its local
ML models from Hugging Face the first time it starts -- a bge-m3 embedding model
and a cross-encoder reranker (quantized ONNX by default; several hundred MB
each, up to ~2.3 GiB if you switch the embedder to the FP32 variant). They land
under `<data dir>/engram/models/<model-name>` (e.g.
`~/.local/share/engram/models/bge-m3` on Linux), and future restarts skip the
download once the files are present. For air-gapped or pre-staged deployments,
set `KLEOS_EMBEDDING_OFFLINE_ONLY=1` to make a missing model file a hard error
instead of a network fetch, and pre-stage the files yourself (`KLEOS_EMBEDDING_MODEL_DIR`
/ `KLEOS_RERANKER_MODEL_DIR` control where they're expected). Point `KLEOS_EMBEDDING_URL`
and/or `KLEOS_RERANKER_URL` (with `KLEOS_RERANKER_BACKEND=http`) at a remote
provider instead, and the server skips its local download and ONNX runtime
entirely for that model. To leave the whole local inference stack out of the
binary, build with `--no-default-features` (the default-on `ml` cargo feature
gates the ONNX/LanceDB stack; retrieval degrades to FTS + sqlite-vec and the
remote providers above).
**Bootstrap your admin key (one-time):**
bash curl -X POST http://localhost:4200/bootstrap \ -H "Content-Type: application/json" \ -d '{"secret": "pick-a-secret"}'
**Store a memory:**
bash curl -X POST http://localhost:4200/store \ -H "Authorization: Bearer YOUR_KEY" \ -H "Content-Type: application/json" \ -d '{"content": "Production DB is PostgreSQL 16 on db.example.com:5432", "category": "reference"}'
**Search by meaning:**
bash curl -X POST http://localhost:4200/search \ -H "Authorization: Bearer YOUR_KEY" \ -H "Content-Type: application/json" \ -d '{"query": "database connection info"}' ```
For Claude Code hooks, encryption setup, the session sidecar, and client SDKs, see the Getting Started guide.
</details>
<details> <summary><strong>For developers: integration and architecture</strong></summary>
<br>
```bash
The installer (kleos-install or kleos-install-gui) supports four profiles:
| Profile | Includes |
|---|---|
Server | kleos-server, kleos-cli |
Agent Host | kleos-cli, kleos-sh, agent-forge, eidolon-supervisor, cred, kleos-credd |
Full | Every binary |
Custom | Pick individual components |
</details>
---
cargo build --release -p kleos-cli -p kleos-sh -p kleos-cred -p kleos-credd \ -p agent-forge -p eidolon-supervisor
The hooks/ bundle is under maintenance and not currently shipped. For session-start (and other lifecycle) integration today, call the kleos-cli hook subcommands directly from your own hook scripts -- kleos-cli hook session-start, user-prompt, stop, pre-tool, post-tool, and post-bash are supported and documented in docs/KLEOS_OPERATIONS_MANUAL.md. The mandatory-rules text these hooks inject is operator-configurable via the KLEOS_MANDATORY_RULES environment variable on the server. A new hooks bundle will ship once the surface stabilises.
高质量的MCP工具,适合智能代理开发
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,Kleos 是一款质量优秀的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 | Kleos |
| 原始描述 | 开源MCP工具:High-integrity backbone for agentic reasoning, deterministic coordination, and a。⭐10 · Rust |
| Topics | ai-agentsai-memoryknowledge-graphllmmcprust |
| GitHub | https://github.com/Ghost-Frame/Kleos |
| License | NOASSERTION |
| 语言 | Rust |
收录时间:2026-05-25 · 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。
选择 Agent 类型,复制安装指令后粘贴到对应客户端