dekko

MCP serverAI & models

Lets your agent generate a code map of any repository as MAP.md and map.json files.

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About this server

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

Getting started

  1. Save this item in Your setup as a reference.
  2. Read the source or reference documentation for its setup requirements. Saving it here does not connect it to your AI.
  3. Check this page for availability before trying to install it through ahel.

From the project's README

As published by aahlijia/dekko in README.md.

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 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: 3x-200x fewer tokens than a plain Read/Grep workflow for the same task, measured across 7 real, unmodified open-source repos. 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), dekko's structured queries used 3x–200x fewer tokens than the equivalent Read/Grep workflow for the same task (repo orientation, outlining a large file, tracing a symbol's callers/callees).

TaskExample repo (scale)dekkoRead/GrepSavings
Repo orientation (summary)awesome-go (10 files)308 tok~15,271 tok~50x
Repo orientation (summary)cline (2,730 files)1,202 tok~4,020 tok~3.3x
Outline a large fileclaude-code main.tsx (4,683 lines)1,017 tok200,981 tok~197x
Outline a large filezed editor.rs (12,554 lines)1,996 tok115,109 tok~58x
Symbol lookup (query_symbol + callers/callees)tensorflow Graph class~811 tok61,656 tok~76x
Symbol lookup (query_symbol + callers/callees)spring-boot prepareContext759 tok~18,460 tok~24x
Bundled context (workset)zed2,984 tok~5,903+ tok (targeted) / ~164,571 tok (whole file)~2x / ~55x
Bundled context (workset)awesome-go617 tok~6,136 tok~10x

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 ~3,500-symbol codebase from a cold cache takes about 1.8 seconds; queries against the resulting map return instantly. The win isn't universal — small, self-contained files and already-grep-friendly local symbols see little to no benefit, and a few cases in the raw data are void because the cheap answer was also an incomplete one. See benchmarks/real-world-repos/ for the full per-task breakdown, methodology, and correctness caveats.

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

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

Extras (dekko[all] for ~55 more languages, dekko[search] for embedding search), installing from a local clone, and uninstalling are in docs/install.md.

Quick start

cd my-project
dekko map                  # writes .dekko/MAP.md + .dekko/map.json
dekko 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, Rust), dekko map will say so per file; install dekko[all] for ~55 more languages (see Install) and re-run.

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

Signals

GitHub stars
5
Last commit
Oct 2026
Advanced
Delivery
dekko MCP server → your ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
io-github-aahlijia-dekko
Source
github.com/aahlijia/dekko