FATSEARCH

io.github.fatsearchPublished by GitHub account fatsearchv0.2.5Updated Nov 7, 2026

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

Overview

AI-generated overview

Fetches web pages, PDFs and documents and returns them as small, clean, cached Markdown outlines that an assistant can read section by section.

What you can do
  • Fetch a URL and get a clean Markdown outline cached under a short id, then read one section, filter inside the page, or list and follow numbered links
  • Run web searches and GitHub repository searches that return results as ids
  • Read local PDF files, one section per page
  • Render or unblock hard pages (JS shells, captchas, walls) through a configured provider, cheapest first
  • Show per-fetch stats (provider, latency, cost, tokens) and preview what a fetch would run and cost
When to use it
Useful when an assistant needs to read real web pages or PDFs without flooding its context, especially pages a built-in fetch cannot open, and when you want repeatable, low-token page reading with visible per-page cost.
Requirements
Local binary installed via Homebrew, npm, cargo or the install script; runs over stdio as a local process. No account is needed for plain HTTP fetching. Optional provider keys (Oxylabs, Bright Data, Decodo, GitHub) are saved through a local setup form into auth.json; web search needs an Oxylabs or Bright Data key. Bright Data also uses a zone name (BRIGHTDATA_UNLOCKER_ZONE).
Before you install
Provider keys are stored in auth.json on disk rather than an OS keychain, and the setup flow asks you to paste keys into a local browser form, never into chat. Provider calls cost money per page (roughly $0.001–$0.0065), so check dry-run and stats output. Anonymous telemetry is on by default and can be disabled. Pages behind logins are not accessible, and DOCX/XLSX and scanned PDFs are unsupported.

Installation

In SourceWeft

  1. Open FATSEARCH in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

[FATSEARCH: the ripgrep of web searching for AI agents.]

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.


[crates.io] [npm] [release] [license]


[Same question, same answer: FATSEARCH puts 1,384 tokens in the agent's context, Firecrawl puts the whole page, 112,517.]

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 <provider> 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.

console
$ fats setup decodo= setup decodo · waiting for the key at http://127.0.0.1:59802/k/e0c8baba7a5b058947f4fdab97dabb05/decodo · 30 min · $0tell 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 Savethen: 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 · <its URL>) 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.

console
$ fats https://www.nytimes.com/ dry:truenytimes.com/ fetch plain → oxy (after a captcha) → bd ∥ oxyjs after 5s → new u1 · up to $0.0040
$ fats statsu1 rust-lang.org · Rust Programming Language · plain 230ms $0.0000 · 1.2ktoku2 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 · INSTALL2 · KEYS (optional)3 · PLUG IN
brew install fatsearch/tap/fatsearchfats setupclaude 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.

sh
fats setup mcp claude                                             # or codex, cursor: fats adds itselfclaude mcp add --scope user fats -- fats mcp                      # Claude Codecodex 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 <url>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.

sh
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 → Settings → Telemetry, with fats setup telemetry off, FATS_TELEMETRY=0 or DO_NOT_TRACK=1. Details: docs/telemetry.md


17–21 MB binary    4 ms start    5 ms cached read    $0 plain pages    $0.001–0.0065 hard pages (three keys)

17 MB (macOS arm64) to 21 MB (Linux x86_64) · 4 ms native; the npm shim adds Node's ~40 ms
no daemon · no browser · anonymous usage stats (off: fats setup telemetry off · FATS_TELEMETRY=0 · DO_NOT_TRACK=1) · every run →


What it doesn't do (yet)
  • match:near / match:topic: needs a local model
  • OCR for scanned PDFs → ! no_text
  • DOCX / XLSX → ! not_in_v1 zip
  • OS keychain: keys live in auth.json (mode 0600)
  • Remote MCP: stdio only
  • Logins: a page behind a login stays behind it

Each prints a ! row explaining what's missing and what to do. Never silence.


fatsearch.com

reference · benchmarks · changelog · security · contributing

MIT or Apache-2.0, at your option.

Source: README.md at commit 69f298a

Tools

0
SourceWeft started this package once in an isolated sandbox, without credentials, to list its tools. That failed: the package type cannot run in the sandbox.

Version history

6
  1. v0.2.5LatestNov 7, 2026
  2. v0.2.4Oct 22, 2026
  3. v0.2.3Oct 21, 2026
  4. v0.2.2Oct 21, 2026
  5. v0.2.0Oct 20, 2026
  6. v0.1.2Oct 17, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts