Dekko MCP server

<!-- mcp-name: io.github.aahlijia/dekko -->

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.

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:

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.md — a human-readable map: a per-directory overview, an

• 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).

Shortened. The full README is on GitHub.