
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
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).
Installation
In SourceWeft
- Open FATSEARCH in the dashboard and add it to a workspace.
- 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
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.
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.
fats stats is the marketing: real numbers, not claims.
38 hard pages social · news · shops · travel · classifieds · search · one run each
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
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 isfats(likeripgrep→rg). Homebrew, npm and the install script also addfatsearchas a second name for it;cargo installadds onlyfats. No account needed. Without a provider key,fatsreads 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).
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.
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
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.
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.
reference · benchmarks · changelog · security · contributing
MIT or Apache-2.0, at your option.
Source: README.md at commit 69f298a
Tools
0Version history
6- v0.2.5LatestNov 7, 2026
- v0.2.4Oct 22, 2026
- v0.2.3Oct 21, 2026
- v0.2.2Oct 21, 2026
- v0.2.0Oct 20, 2026
- 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