Dekko

io.github.aahlijia由 GitHub 账号 aahlijia 发布v1.9.0更新于 Oct 24, 2026

Static code map generator: MAP.md + map.json for any repo, plus a Claude Code /map plugin

已验证STDIO仅桌面知识与记忆开发者工具

概览

AI 生成的概览

Dekko 为代码仓库生成静态代码地图与调用图,让助手用远少于读文件的 token 回答代码库问题。

可以做什么
  • 生成仓库地图:用 tree-sitter 扫描仓库,输出可读的 MAP.md 和机器可读的 map.json。
  • 概览代码库:获取目录、热点与入口点的简短摘要。
  • 查看文件与目录:无需逐行阅读即可列出大文件或目录的结构。
  • 追踪符号:查询某函数被谁调用、调用了谁,以及外部 API 的使用情况。
  • 为某个符号或任务打包上下文。
适用场景
适合助手在大型或不熟悉的仓库中工作,需要快速定位、列出文件大纲或追踪调用关系,又不想花 token 通读整个文件时。对小型、自包含的文件或 grep 已能轻松处理的符号,收益有限。
运行要求
以 stdio 本地进程运行,从 PyPI 安装(uvx、uv tool install、pip 或 pipx),需要 Python 运行时。未声明账号、API 密钥或环境变量。更多语言支持需安装 dekko[all] 附加包,向量检索需 dekko[search]。
安装前请注意
会在本地扫描仓库源码,并在项目中写入 .dekko/ 目录(默认被 git 忽略)。可选附加包会引入额外依赖。未声明需要凭据或网络访问。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Dekko,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

[dekko]

[CI] [PyPI] [Downloads] [Python] [License: MIT] [Ruff]

Ever watched your coding agent grep blind through a repo, open three files it didn't need, and burn fifteen thousand tokens just to answer "who calls this function"? That's the problem dekko exists to fix.

[dekko demo: mapping a repo and querying a symbol in seconds]

This demo runs on dekko's own repo (commit 835733c) — clone it and run the same three commands yourself.

dekko is a fast, offline, dependency-free static code map generator and codebase indexer for LLM coding agents. It scans a repository with tree-sitter (no model tokens spent parsing) and writes:

  • MAP.md — a human-readable map: a per-directory overview, an embedded architecture diagram, load-bearing/orchestrator rankings, then every file's functions/methods with signatures, doc lines, and who calls and is called by whom.
  • map.json — the same graph in machine-readable form.

On top of the map, dekko gives an agent a token-cheap way to answer questions like "what does this file contain," "who calls this function," and "what do I need to safely change this" — without reading whole files. It ships as a CLI, a Claude Code /map plugin + MCP server (Model Context Protocol), and works with Cline too.

The result: 10x-300x fewer tokens than a plain Read/Grep workflow on the everyday tasks (orientation, outlining a large file, a symbol's callers), measured across 7 real, unmodified open-source repos on dekko 0.43.77. The floor, a small grep-friendly local symbol, is about 2.5x. The full breakdown is right below.

Why dekko?

Most agent workflows gather context by reading whole files or grepping across a repo — expensive, and it throws away structure (who calls what, what a function's fan-in/fan-out looks like). dekko instead parses the repo once into a call graph and answers targeted questions against it. Measured across 7 real, unmodified open-source repos (Go, TypeScript, Java, Rust, Python/C++ — up to 14k files, 172k symbols) on dekko 0.43.77, dekko's structured queries used 10x–300x fewer tokens than the equivalent Read/Grep workflow for the same task (repo orientation, outlining a large file, tracing a symbol's callers).

TaskExample repo (scale)dekkoRead/GrepSavings
Repo orientation (summary)awesome-go (10 files)359 tok~16,328 tok~45x
Repo orientation (summary)claude-buddy (57 files)~349 tok~113,514 tok (every source file)~325x
Outline a large fileclaude-code REPL.tsx (5,005 lines)~1,154 tok~223,963 tok~194x
Outline a large filecline SdkController.ts (84 KB)1,803 tok~21,023 tok~11.7x
Outline a directoryzed crates/git_ui/src (32 files)~35,778 tok~418,520 tok~11.7x
Callers of a symbolclaude-code errorMessage~602 tok~18,521 tok (323+ grep hits)~31x
Callers of a symbolzed MultiWorkspace.new (22 sites, 8 files)~809 tok~381,446 tok (read the caller files)~471x
External-API usageclaude-code chalk~798 tok~8,099 tok~10x
Bundled context (workset)awesome-go ToHTML263 tok4,104 tok~16x

dekko's cost stays roughly flat per query while Read/Grep scales with file/repo size, so the ratio grows with scale. It's fast in wall-clock terms too: mapping dekko's own ~4,300-symbol codebase from a cold cache takes about 5 seconds on all cores, an incremental remap after an edit is well under a second, and queries against the resulting map return instantly. The win isn't universal — small, self-contained files and already-grep-friendly local symbols see little benefit (the floor measured was about 2.5x). See benchmarks/real-world-repos/ for the full per-task breakdown, methodology, the original 2026-08 study, and the correctness caveats it raised and how they were closed.

Compared to tag-index tools like ctags/gtags, dekko resolves actual call edges (not just definitions), ranks files by load-bearing-ness, and speaks directly to agents over MCP or the CLI — no editor plugin required.

Install

sh
uv tool install dekko      # or: pip install dekko / pipx install dekkodekko --claude-install     # add the /map command + MCP server to Claude Code, then restart

Extras (dekko[all] for 43 more languages, dekko[search] for embedding search), installing from a local clone, and uninstalling are in docs/install.md.

Quick start

sh
cd my-projectdekko map                  # writes .dekko/MAP.md + .dekko/map.jsondekko summary               # ~40-line digest: dirs, hotspots, entry points

.dekko/ is git-ignored by default; the map regenerates on demand, so you rarely need to run dekko map again by hand. If your repo has languages outside the default Tier-1 set (Python, C, C++, JS/TS, Go, Java, Kotlin, Rust), dekko map will say so per file; install dekko[all] for 43 more languages (see Install) and re-run. The list says how well each one is read.

Documentation

  • docs/install.md — installation, extras, local clone, uninstall
  • docs/cli.md — every CLI command, symbol targets, excluding files, notes, daemon mode, language support
  • docs/claude-code.md — the /map plugin, push hooks, Claude Code skills, the MCP server, and Cline

Learn more

  • CHANGELOG.md — per-version history
  • CONTRIBUTING.md — dev setup, testing, releasing
  • benchmarks/ — token-efficiency measurements, including a 7-repo real-world comparison against a plain Read/Grep workflow

来源:README.md,提交 6d46175

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

11
  1. v1.9.0最新Oct 9, 2026
  2. v1.8.0Oct 7, 2026
  3. v1.7.0Oct 6, 2026
  4. v1.6.0Oct 2, 2026
  5. v1.5.0Sep 27, 2026
  6. v1.3.0Sep 26, 2026
  7. v1.2.0Sep 25, 2026
  8. v1.1.0Sep 24, 2026
  9. v1.0.0Sep 22, 2026
  10. v0.43.71Sep 22, 2026
  11. v0.43.49Sep 16, 2026

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