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PopNx MCPMCP servers for people who use AI · explained in plain words

FATSEARCH

by fatsearchversion 0.2.5i★ 144iRuns on your computer
Registry nameio.github.fatsearch/fats

How to install

Overview

Description from the maker (original English)

Web pages, PDFs and documents as small, clean, cached Markdown for AI agents

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Docs, sheets & office work

Install

Pick the AI app you use, then copy the settings.

Passed 2/2 checks · Runs on your computer

First: which AI do you use?

Pick your app and the steps appear below.

Claude cannot connect FATSEARCH yet

The maker has not listed install details in the MCP Registry yet

ChatGPT cannot connect FATSEARCH yet

The maker has not listed install details in the MCP Registry yet

What you can do instead

B · Others in Docs, sheets & office work that work with ChatGPT

Picked from the most used in the same category, only ones that connect by address with no key

Claude Code cannot connect FATSEARCH yet

The maker has not listed install details in the MCP Registry yet

Cursor cannot connect FATSEARCH yet

The maker has not listed install details in the MCP Registry yet

VS Code cannot connect FATSEARCH yet

The maker has not listed install details in the MCP Registry yet

Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.

See every app that uses MCP →

JSON settings are under “For developers” below

Stuck? Ask people who use FATSEARCH💬 Discussion →
For developers: Terminal commands and JSON settings

Values you fill in

  • BRIGHTDATA_UNLOCKER_ZONE env
    Bright Data Web Unlocker zone name (optional; fats setup bd saves the account's zone)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

At a glance

Downloads per weeki
Not on npm/PyPI
Licencei
No licence stated
Connection
Runs on your computer
Latest versioni
0.2.5
Published to registryi
Nov 7, 2026
Code last changedi
Nov 7, 2026
Maker
fatsearch
Packages
cargo: fatsearch
Registry status
Active

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Run on your computer in

GooseLM StudioMsty StudioCherry StudioVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

All apps, with pros and cons →

Related guides

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 11, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account fatsearch, which owns the repo

  • ✓ Pass

    Still maintained

    Code last changed 4 days ago

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Discussion

Ask, share a tip or report that it does not work. Sorted by what people marked helpful.

No posts yet. Be the first to ask or share.

Posts here are written by users, not the PopNx team.

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User reviews

No reviews yet

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Compared with others in Docs, sheets & office worki

  • More stars than 99% of the other 3749 servers in this category
  • Published to the registry more recently than 85% of the other 3749 servers in this category
  • Basic checks equal to or better than 100% of the other 3749 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is FATSEARCH safe?

It passed 2 of 2 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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed 4 days ago, and the latest version (0.2.5) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Rust on your computer.

What can I use instead?

In the same category: Puter MCP, XcodeBuildMCP, XcodeBuildMCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Puter MCP

Puter MCP enables AI tools to interact with Puter: manage files, websites, workers, and more

by HeyPuterWidely used★ 44.1KUpdated 5 months ago

Runs in the cloud✓ puter.com

XcodeBuildMCP

XcodeBuildMCP provides tools for Xcode project management, simulator management, and app utilities.

by getsentryWidely used↓ 130.5K/wk★ 6.6KUpdated 4 months ago

Runs on your computer✓ xcodebuildmcp.com

XcodeBuildMCP

XcodeBuildMCP provides tools for Xcode project management, simulator management, and app utilities.

by cameroncookeWidely used↓ 130.5K/wk★ 6.6KUpdated 14 months ago

Runs on your computer

README from the maker

Open the README

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.

Reads the pages your agent's built-in fetch can't (JS pages, PDFs) through your own provider key,

kept on disk as clean Markdown, navigated by outline and ids.

same question · same answer · 81× less context

That's the point.

Every page your agent reads costs you this

Wikipedia · Rust · model input at $2 / M tokens (Claude Sonnet 5.5, 2026-10-19)Tokens in contextFetchModel bill
Firecrawl112,5171 credit$0.23
Bright Data Unlocker103,6251 request$0.21
Oxylabs Web API102,6091 request$0.21
Tavily Extract97,5040.2 credit$0.20
Jina Reader94,415free$0.19
FATSEARCH918$0$0.002

Your agent gets a short outline. It reads one section when it needs depth, not the whole page.

Menus, cookie banners, navigation, footer links, tracking scripts: gone.

Prices, dates, numbers: kept (loss guard counts every one) .

[!TIP]

The "free" fetch costs ~100× more at the model. And it stays in context, every turn after.

Your key never touches the chat

fats setup opens a one-time key form on 127.0.0.1, behind a random token, for 30 minutes.

You paste the key there in your browser, so it stays out of the chat, the model's context and the agent's logs.

The form refuses a POST from another origin; the key is checked live, saved with mode 0600, sent only to its provider.

$ fats setup decodo

= setup decodo · waiting for the key at http://127.0.0.1:59802/k/e0c8baba7a5b058947f4fdab97dabb05/decodo · 30 min · $0 tell the user (never ask for the key in chat):

  1. open https://dashboard.decodo.com/web-data/playground (no account yet: https://dashboard.decodo.com/register)
  2. Copy the API key shown on the Web Data playground. Do NOT paste it in this chat.
  3. open http://127.0.0.1:59802/k/e0c8baba7a5b058947f4fdab97dabb05/decodo , paste the key, press Save

then: fats setup (when the user says done; end your turn, do not poll · checks it, $0) link dead (30 min passed)? run fats setup decodo again and give the user the new line 3

fats setup shows a form still waiting (! form_waiting decodo · 23 min left · ) or one whose time ran out (! form_expired decodo · the link the user got is dead → fats setup decodo · new link, same 3 steps). Over SSH (SSH_CONNECTION or SSH_TTY set) one more line says how to paste the key in a terminal there.

On hard pages

fats tries plain HTTP first (free). If the page is a JS shell, a captcha, or a wall, it climbs to your providers: cheapest first, hedged, with cost tracking on every call.

$ fats https://www.nytimes.com/ dry:true

nytimes.com/ fetch plain → oxy (after a captcha) → bd ∥ oxyjs after 5s → new u1 · up to $0.0040

$ fats stats u1 rust-lang.org · Rust Programming Language · plain 230ms $0.0000 · 1.2ktok u2 en.wikipedia.org · Rust (programming language… · plain 558ms $0.0000 · 40.9ktok

fats stats is the marketing: real numbers, not claims.

38 hard pages social · news · shops · travel · classifieds · search · one run each

answer in the returned text, within1 s10 s20 s60 s
FATSEARCH 0.2.0 2026-10-2112191935 /38
Firecrawl 2026-10-160222424
Tavily 2026-10-169171819

FATSEARCH reads more of the hard pages; Firecrawl and Tavily are faster on the pages they do read (same pages, medians: 23.7 s vs 4.9 s, 23.7 s vs 1.0 s). Readers ran on different days. Method and every row → · the table above: one page, six readers →

Tested in agents FATSEARCH 0.1.3 · Claude Code 2.1.280, one run each, 2026-10-19

  • 51 tasks, FATSEARCH MCP vs Firecrawl MCP: 50/51 vs 51/51 right · $15.06 vs $53.48 per 1k tasks · median 5.3 s vs 6.7 s · slowest tenth 43.8 s vs 21.5 s. Details →
  • Claude Code's WebFetch got 403 on npm, Medium and G2; FATSEARCH read all three. Details →
  • One Wikipedia page, open-source readers: FATSEARCH 1,384 tokens to the answer; mcp-server-fetch, Crawl4AI, mcp-searxng and self-hosted Firecrawl 75k–117k for the whole page. Details →
  • Full tables, losses included: docs/benchmarks.md

Get started

| 1 · INSTALL | 2 · KEYS (optional) | 3 · PLUG IN | |:-:|:-:|:-:| | brew install fatsearch/tap/fatsearch | fats setup | claude mcp add --scope user fats -- fats mcp |

or curl -fsSL https://fatsearch.com/install.sh | sh · Windows: npm i -g fatsearch · cargo install --locked fatsearch · every host →

[!NOTE]

The package is fatsearch; the command is fats (like ripgrep → rg). Homebrew, npm and the install

script also add fatsearch as a second name for it; cargo install adds only fats.

No account needed. Without a provider key, fats reads what a plain request gets; web search needs an Oxylabs or Bright Data key.

With any one key (Oxylabs, Bright Data or Decodo) it renders and unblocks pages through that provider.

Setup

You, at a terminal: run fats setup. It is a menu (↑↓ Enter): the free fetch and each provider with its state, then Settings (agent connection, cache, stats, telemetry). Pick a provider, paste its key (shown as • and a count), and fats checks it live before it saves it. fats setup oxy jumps straight to one (also bd, decodo, gh).

Your agent, or no terminal: the agent runs fats setup oxy (or bd, decodo, gh). It prints the provider's dashboard link and a one-time form on 127.0.0.1, open for 30 minutes. The agent gives you the URL; you paste the key into the form in your browser, never into the chat (what it prints). Then the agent runs fats setup to check it ($0).

Keys go to auth.json in the key dir (mode 0600) and are sent only to their provider. `auth.json` is the one key source: fats never sends a key from the environment, so the key you saved is the key every call uses (fats shows each one's last 4 characters: keys oxy …6XBR · bd none · decodo none · gh none · auth.json). On a machine without a browser (CI, SSH), pipe the key in: printf %s "$KEY" | fats setup oxy checks it and saves it. Keys already exported: run fats setup import-env once: it checks them, copies them in where no key is saved, and never replaces a saved one. Replacing a key keeps the old file as auth.json.bak (0600).

ProviderKeyPage, no JSPage, renderedWeb search
free (plain HTTP, your IP)none$0——
Oxylabs Web APIfats setup oxy (import: OXYLABS_WEB_API_KEY)$0.0010$0.0015$0.0010
Bright Data Web Unlockerfats setup bd (import: BRIGHTDATA_API_KEY; zone BRIGHTDATA_UNLOCKER_ZONE)—$0.0015$0.0015
Decodo Web Data APIfats setup decodo (import: DECODO_AUTH_TOKEN)$0.0010$0.0015—
GitHub (fats gh)fats setup gh copies the gh CLI's token (import: GH_TOKEN)$0——

List prices per page, the ones dry:true and fats stats use. Oxylabs and Bright Data spend can be checked with fats account; Decodo has no usage read for this key, so its $ is the list price, never reconciled.

Turn one off without losing its key: fats setup oxy off, back with fats setup oxy on.

The free fetch is your own connection: one request per page from your IP, at most one start per site per second; a page waits its turn rather than buying a provider call. Providers use their own IPs and have no pace. fats setup free off sends every page to a provider instead, so every page costs.

MCP

One tool. One string. Same commands.

fats setup mcp claude                                             # or codex, cursor: fats adds itself

claude mcp add --scope user fats -- fats mcp # Claude Code codex mcp add fats -- fats mcp # Codex {"mcpServers": {"fats": {"command": "fats", "args": ["mcp"]}}} # Cursor, Desktop, …

The tool is fats(cmd) and its card is ~60 tokens. An agent that knows fats u1#3 knows the whole tool.

MCP Registry: mcp-name: io.github.fatsearch/fats

Commands

CommandDoes
fats fetch → clean → outline, cached as u1
fats u1#3read section 3
fats u1 pricefilter inside the page
fats u1 links · fats l4numbered links · follow one
fats rust async runtimeweb search → results as ids
fats gh rust markdownGitHub repos by stars
fats ./report.pdflocal file, one section per page
fats statsevery fetch: provider, ms, cost, tokens
… dry:truewhat would run, what it would cost

mods limit:20 country:de js:true wait:30 fresh:true · one screen of all of it: fats help · how to use it well: fats guide

For agents

The agent skill is versioned in this repo (skills/fatsearch/SKILL.md): how to read pages without flooding context, and how to install, connect and verify fats when it is missing.

npx skills add fatsearch/fatsearch        # Agent Skills standard: Claude Code, Codex, Cursor, Copilot, Gemini CLI, …

gh skill install fatsearch/fatsearch # the same through GitHub CLI ≥ 2.90

An agent without either CLI reads it pinned to a release: https://raw.githubusercontent.com/fatsearch/fatsearch/v0.2.5/skills/fatsearch/SKILL.md. That way the agent sees versioned text it can review, and nothing it runs comes from a website.

Docs as plain Markdown for agents: fatsearch.com/llms.txt.

Telemetry

FATSEARCH shares anonymous usage stats so we can fix what breaks. It never shares what you read or search.

  • Never sent: URLs, searches, page text, files, API keys, your IP address, any id.
  • Sent: fatsearch version, OS, which package (npm, Homebrew, cargo…), commands used, errors, which providers worked, crashes in our code.

See exactly what's sent with fats telemetry show. Turn it off in `fats setup → Sett

Only the beginning is shown; read the rest in the repo