curl -fsSL https://loct.io/install.sh | sh # One-liner (installs from crates.io)或者直接通过 Cargo 安装：
cargo install loctree # CLI: loct, loctree
cargo install loctree-mcp # MCP server for AI agentsRelated MCP server: MCP Codebase Server
工件默认存储在您的操作系统缓存目录中（可通过 LOCT_CACHE_DIR 覆盖）。
loct # Scan project, write cached artifacts
loct --for-ai # AI-optimized overview (health, hubs, quick wins)
loct slice src/App.tsx --consumers # Context: file + deps + consumers
loct find useAuth # Find symbol definitions
loct find 'Snapshot FileAnalysis' # Cross-match: where terms meet
loct impact src/utils/api.ts # What breaks if you change this?
loct health # Quick summary: cycles + dead + twins
loct dead --confidence high # Unused exports
loct cycles # Circular imports
loct twins # Dead parrots + duplicates + barrel chaos
loct audit # Full codebase reviewloctree 通过单次扫描捕获项目的真实依赖图，随后即可从快照中即时回答结构性问题。专为需要聚焦上下文而无需阅读每个文件的 AI 智能体而设计。
核心能力：
全息切片 (Holographic Slice) - 一次调用即可提取文件 + 依赖项 + 使用者
交叉匹配搜索 (Cross-Match Search) - 查找多个术语共同出现的位置（非简单的 grep）
死代码导出检测 (Dead Export Detection) - 查找 JS/TS、Python、Rust、Go、Dart 中未使用的导出
循环引用检测 (Circular Import Detection) - 使用 Tarjan 的 SCC 算法捕获运行时炸弹
处理程序追踪 (Handler Tracing) - 追踪 Tauri 命令在整个前端/后端管道中的流向
影响分析 (Impact Analysis) - 在删除或重构之前查看会产生什么影响
jq 查询 - 使用 jq 语法查询快照数据 (loct '.files | length')
loctree 作为 MCP 服务器发布，可与 AI 智能体无缝集成：
loctree-mcp # Start via stdio (configure in your MCP client)工具：repo-view、slice、find、impact、focus、tree。每个工具都接受一个 project 参数——首次使用时自动扫描，并将快照缓存在内存中。
{
"mcpServers": {
"loctree": {
"command": "loctree-mcp",
"args": []
}
}
}语言 | 死代码导出准确度 | 备注 |
Rust | ~0% FP | 在 rust-lang/rust (35K 文件) 上测试 |
Go | ~0% FP | 在 golang/go (17K 文件) 上测试 |
TypeScript/JavaScript | ~10-20% FP | JSX/TSX, React 模式, Flow, WeakMap |
Python | ~20% FP | 库模式, |
Svelte | <15% FP | 模板分析, .d.ts 重导出 |
Vue | ~15% FP | SFC 支持, Composition & Options API |
Dart/Flutter | 完全支持 | pubspec.yaml 检测 |
自动从 Cargo.toml、tsconfig.json、pyproject.toml、pubspec.yaml、src-tauri/ 检测技术栈。
为任何文件提取 3 层上下文：
loct slice src/App.tsx --consumersSlice for: src/App.tsx
Core (1 files, 150 LOC):
src/App.tsx (150 LOC, ts)
Deps (3 files, 420 LOC):
[d1] src/hooks/useAuth.ts (80 LOC)
[d2] src/contexts/AuthContext.tsx (200 LOC)
[d2] src/utils/api.ts (140 LOC)
Consumers (2 files, 180 LOC):
src/main.tsx (30 LOC)
src/routes/index.tsx (150 LOC)
Total: 6 files, 750 LOC多术语查询显示术语相交的位置，而非简单的 OR 逻辑：
loct find 'Snapshot FileAnalysis'=== Cross-Match Files (9) ===
src/snapshot.rs: Snapshot(6), FileAnalysis(4)
src/slicer.rs: Snapshot(2), FileAnalysis(3)
...
=== Symbol Matches (222 in cross-match files) ===
src/snapshot.rs:20 - Snapshot [struct]
src/types.rs:15 - FileAnalysis [struct]
...
=== Parameter Matches (4 cross-matched) ===
src/slicer.rs:45 - snapshot: &Snapshot in build_slice(analyses: &[FileAnalysis])直接查询快照数据：
loct '.dead_parrots' # Dead code findings
loct '.files | length' # Count files
loct '.edges[] | select(.from | contains("api"))' # Filter edges
loct '.summary.health_score' # Health scoreloct lint --fail --sarif > results.sarif # SARIF for GitHub/GitLab
loct --findings | jq '.dead_parrots | length' # Check dead code count
loct doctor && echo 'Clean' # Health gateCrate | 描述 |
核心分析器 + CLI ( | |
HTML 报告渲染器 (Leptos SSR) | |
面向 AI 智能体的 MCP 服务器 |
make precheck # fmt + clippy + check (run before push)
make install # Install loct + loctree-mcp
make test # Run all workspace tests
make publish # Cascade publish to crates.io[](https://crates.io/crates/loctree)MIT 或 Apache-2.0。请参阅 LICENSE-MIT 和 LICENSE-APACHE。
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