AI Skill Hub 强烈推荐：Enola 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。
Enola 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。
Enola 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/enola-labs/enola
# 方式二：手动配置 claude_desktop_config.json
{
"mcpServers": {
"enola": {
"command": "npx",
"args": ["-y", "enola"]
}
}
}
# 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 Enola 执行以下任务... Claude: [自动调用 Enola 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": {
"enola": {
"command": "npx",
"args": ["-y", "enola"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
A deterministic structural model of your codebase for AI coding agents — your real architecture, extracted from source, not guessed.
enola is a local Model Context Protocol (MCP) server. Point it at one or more repositories and it builds a precise graph of your code's architecture — modules, types, routes, dependencies, and how they all connect — straight from your source. It then exposes tools your AI agent can use to read, traverse, query, and reason over that structure. So before your agent writes a line of code, it already knows the shape of the thing it's editing.
---
Grab a prebuilt binary — no Go toolchain or C compiler required:
curl -fsSL https://raw.githubusercontent.com/enola-labs/enola/main/install.sh | shThis installs enola to ~/.local/bin. If that's not on your PATH, add it:
export PATH="$HOME/.local/bin:$PATH"Binaries are published for Linux, macOS (amd64/arm64), and Windows (amd64). You can also download a specific build from the Releases page, or build from source.
Prerequisites: Go 1.25+ and a C compiler (for the tree-sitter bindings).
go build -o enola ./cmd/enola # or: go install ./cmd/enolaTo run a one-shot snapshot without starting the MCP server:
enola --generate [config_path] # config_path is optional; defaults to mcp-arch.yaml, falling back to built-in defaults if absentArtifacts are written to the configured output.dir (default .enola/). The config file is optional — see ARCHITECTURE.md → Configuration for the full field reference and defaults.
---
enola needs no config file. Every setting has a built-in default, so out of the box it indexes the current repo with all extractors enabled and writes to .enola/. A config file (mcp-arch.yaml) only overrides those defaults — it never adds capability you'd otherwise lack. When enola can't find one it simply prints warning: …, using defaults and carries on.
The install script installs only the binary, by design — it does not place a config file. Grab the bundled one from the repo whenever you want to customize (tune the ignore globs, pick a subset of extractors, change the output dir, …):
curl -fsSL https://raw.githubusercontent.com/enola-labs/enola/main/mcp-arch.yaml -o mcp-arch.yamlThe examples/ directory has ready-made per-language and multi-repo starting points, and examples/full.yaml documents every option. For the full field reference and defaults, see ARCHITECTURE.md → Configuration.
enola --explain
高质量的MCP工具，架构清晰
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，Enola 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 | enola |
| Topics | mcpai-toolsarchitecturecode-analysisdependency-graphgolangc |
| GitHub | https://github.com/enola-labs/enola |
| License | Apache-2.0 |
| 语言 | C |
收录时间：2026-06-25 · 更新时间：2026-06-25 · 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