GitHub
GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.
Description from the maker (original English)
Static code map generator: MAP.md + map.json for any repo, plus a Claude Code /map plugin
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"dekko": {
"command": "uvx",
"args": [
"dekko",
"serve",
"--mcp"
]
}
}
}Run this in your terminal
claude mcp add dekko -- uvx dekko serve --mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"dekko": {
"command": "uvx",
"args": [
"dekko",
"serve",
"--mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"dekko": {
"type": "stdio",
"command": "uvx",
"args": [
"dekko",
"serve",
"--mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account aahlijia, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.9.0) reached the registry 29 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: GitHub, Desktop Commander, Cloudflare MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.
MCP server for terminal commands, file operations, and process management
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Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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:
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.
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).
| Task | Example repo (scale) | dekko | Read/Grep | Savings |
|---|---|---|---|---|
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 file | claude-code REPL.tsx (5,005 lines) | ~1,154 tok | ~223,963 tok | ~194x |
| Outline a large file | cline SdkController.ts (84 KB) | 1,803 tok | ~21,023 tok | ~11.7x |
| Outline a directory | zed crates/git_ui/src (32 files) | ~35,778 tok | ~418,520 tok | ~11.7x |
| Callers of a symbol | claude-code errorMessage | ~602 tok | ~18,521 tok (323+ grep hits) | ~31x |
| Callers of a symbol | zed MultiWorkspace.new (22 sites, 8 files) | ~809 tok | ~381,446 tok (read the caller files) | ~471x |
| External-API usage | claude-code chalk | ~798 tok | ~8,099 tok | ~10x |
Bundled context (workset) | awesome-go ToHTML | 263 tok | 4,104 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.
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 43 more languages, dekko[search] for embedding search), installing from a local clone, and uninstalling are in docs/install.md.
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, 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.
/map plugin, push hooks, Claude Code skills, the MCP server, and Cline