stalin
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@stalinTurn Hacker News front page into a typed JSON API with title, url, points, and comments."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
☭ stalin
Turn any website into a self-healing, typed JSON API.
He seizes the means of extraction.
Every scraper you have ever written is already dead. It just doesn't know it yet.
Some Tuesday, a frontend dev renames .score to .karma, your pipeline fills
with nulls, and you find out three days later when a dashboard flatlines.
stalin does not tolerate this. You describe what you want in plain English, once. stalin compiles that into CSS selectors, watches them like a paranoid quartermaster, and when the website changes its layout — and it will — stalin detects the drift in microseconds, re-locates your data, proves the fix against five deterministic gates, and keeps shipping typed JSON like nothing happened. The selector was purged. The schema survives. The API never changes shape without your explicit order.
Your scraper doesn't break. It gets reeducated.
The 60-second demo
$ pip install stalin-scraper
$ stalin init
$ stalin add https://news.ycombinator.com -n stories \
--item "each story row on the front page" \
-f "title: str the headline text of each story
url: url the link the headline points to
points: int | null the upvote count
comments: int | null number of comments"
✓ fetched news.ycombinator.com 200 · 41 KB · 0.3s
✓ title .titleline > a verified 30/30 via heuristic · 2 fallbacks
✓ url .titleline a @href verified 30/30 via heuristic · 2 fallbacks
✓ points .score verified 29/30 via heuristic · 2 fallbacks
✓ comments .subline a:last-child verified 30/30 via llm · 2 fallbacks
✓ wrote sources/stories.yml, .stalin/lock.json (schema v1.0.0, 8 fallbacks)
$ stalin run stories | jq '.items[0]'
{ "title": "Show HN: …", "url": "https://…", "points": 312, "comments": 148 }
$ stalin serve
stalin API → http://127.0.0.1:8411
GET /v1/stories typed JSON, schema v1.0.0
GET /openapi.json OpenAPI 3.1
GET /healthz per-source statusAnd then — weeks later, when the site ships a redesign — the moment this tool
exists for. This is a real transcript (demo site renamed every class and
swapped <h2> for <div>):
$ stalin run stories
⚠ drift detected · stories.points
selector .score
signals zero-match
✓ heal title .story .headline ──→ .story .hdr via heuristic
✓ heal url .headline a @href ──→ .hdr a @href via heuristic
✓ heal points .score ──→ .karma via heuristic
✓ heal comments .comments ──→ .replies via heuristic
✓ stories 20 items schema v1.0.0 (4 fields healed)
$ stalin history stories
11:16:16Z ✓ heal points .score ──→ .karma via heuristic · zero-match
11:16:28Z ✓ confirmed pointsFour fields, one redesign, zero human intervention, zero schema changes,
milliseconds of healing. The comrades downstream consuming /v1/stories
never noticed anything.
Related MCP server: web-scraper-server
Why this exists
🩹 It never breaks silently | Five drift signals run on every scrape — including the nasty case where your selector still matches something, just the wrong something. Detection costs microseconds, not LLM calls. |
📐 The schema is law | Fields are typed ( |
🏠 Local-first, zero API keys | The healer runs on your machine through Ollama. No cloud, no per-token bill, no data leaving the building. |
🧠 The LLM is optional | Compile and healing run a ladder: stored fallbacks → DOM-statistics heuristics → local LLM. On most pages the heuristics do everything in milliseconds and the model is never consulted. No Ollama at all? You still get full detection + alerting. |
Any website → a live, queryable API ⚡ new in 0.2
A static_feed gives you one fixed page as JSON. But most of the web you'd
actually want as an API is parameterized — a search box, a profile page,
a lookup by ID. stalin turns those into live typed endpoints. Put a {param}
in the URL and give one example to compile against:
$ stalin add "https://quotes.toscrape.com/tag/{tag}/" -n quotes \
--item "each quote block on the page" \
--example tag=love \
-f "text: str the quote text itself
author: str who said it
tags: list[str] the topic tags on the quote"
✓ fetched quotes.toscrape.com/tag/love/ 200 · 12 KB
✓ text .quote .text verified 10/10 via heuristic
✓ author .author verified 10/10 via heuristic
✓ tags .tags .tag verified 10/10 via heuristic
live lookup — params: tagThat website has no API. It does now:
$ stalin run quotes --param tag=courage --json | jq '.count'
2
$ stalin serve
GET /v1/quotes?tag=humor # live, typed, on demand
GET /openapi.json # the param is a documented query parameter$ curl 'http://127.0.0.1:8411/v1/quotes?tag=love' | jq '.items[0].author'
"André Gide"
$ curl 'http://127.0.0.1:8411/v1/quotes' # missing required param
{"error": "missing required param(s): tag", "params": {"tag": "str"}}And it becomes a typed tool for your agents. Every parameterized source is
auto-exposed over MCP as lookup_<name>(param=…) with a generated input
schema — so Claude (or any agent) calls lookup_quotes(tag="stoicism") and
gets back schema-guaranteed JSON, no scraping code in the agent, no HTML in the
prompt. That's stalin's answer to "why not just let the agent scrape?" — the
tool's contract stays honest even as the site churns.
Lookups self-heal too — the hard version
A live lookup returns different content for every query, so "zero results" can
mean the query was empty or the site broke. stalin distinguishes them: you
declare a not_found signal for legitimately-empty pages (never healed
against, same rule as block pages), and healing is anchored to a heal
fixture — the known-good example params you compiled with. When a real query
comes back unexpectedly empty, stalin re-verifies selectors against the fixture
(stable, known structure), heals there, and re-applies the fix to your query.
Per-query variation never gets mistaken for drift.
Proven live: pointed at a page, compiled, then renamed every CSS class and
swapped the tags — the very next ?param=… request healed three fields against
the fixture and returned correct typed data, in one round, no human touch.
What works today, honestly
live_lookup runs on static-HTML pages right now. Path params (/{id}/)
and query params (?q=…) both work. What it does not do yet, and won't
pretend to: JavaScript-rendered pages (the Playwright engine seam exists but
isn't built), pagination/infinite-scroll, and anything behind a login or
CAPTCHA — those stay refused, by design. It does public, unauthenticated,
static surfaces. That covers a huge amount of "this site should've had an
API" — and none of the stuff that gets you sued.
How healing works
drift detected on field F
├─ Rung 1: stored fallbacks compile-time alternates, ~ms, no LLM
├─ Rung 2: heuristic re-location DOM statistics scored against the
│ field's fingerprint, ~ms, no LLM
├─ Rung 3: LLM re-location local model, sentinel text protocol —
│ works with any Ollama model
└─ Rung 4: broken serve last-good data, exit 3, tell youThe proposers differ per rung. The judge never changes: every candidate selector faces five deterministic acceptance gates —
Schema — every extracted value must cast to the declared type
Cardinality — match counts must stay near the historical baseline
Shape — values must match the field's learned value-pattern (or migrate to a consistent new one, which is recorded)
Anchor — if an old known-good value still exists on the page, the new selector must capture it exactly (substring lookalikes are rejected)
Disjointness & robustness — no annexing another field's selector, no position-brittle
:nth-child(7)nonsense, no auto-generated class hashes
The LLM proposes. The gates dispose. No model opinion is ever trusted about
its own output — every accepted heal was executed against the real DOM and
survived all five gates. Accepted heals are applied immediately (data keeps
flowing) but marked healed-unconfirmed until two clean runs promote them;
a re-drift inside that window reverts the heal and flags the field instead of
thrashing on A/B-tested sites.
Everything is recorded. git diff .stalin/lock.json shows every selector the
healer has ever touched, and .stalin/history/*.jsonl is an append-only,
line-per-event audit log. Rewriting history is for websites, not for your
data pipeline.
Install
pip install stalin-scraperOptional but recommended — a local model for the healing rung:
# any ollama model works; small ones are fine (the gates do the hard part)
ollama pull qwen3:1.7bThen check your environment:
stalin doctorUsage
Command | What it does |
| Scaffold a project ( |
| Compile a new source: fetch → generate selectors → verify → save |
| Compile a live_lookup: any templated URL → a queryable API |
| Run a live lookup for specific params |
| Filter/sort/select/paginate results |
| Query over HTTP (see Query it) |
| Let the local LLM compile a query for you |
| Extract now. Auto-heals on drift. JSON to stdout when piped |
| Detect drift, report, exit 3 — never heal (CI mode) |
| Force a heal pass (includes the LLM rung) |
| HTTP API over cached snapshots + OpenAPI 3.1 |
| Foreground scheduler: run each source on its |
| MCP server on stdio — plug your sources into Claude/any agent |
| Print the JSON Schema; explicitly version-bump the contract |
| The heal/drift/confirm timeline |
| Refresh the reference HTML snapshot |
| Environment + per-source health check |
Exit codes are a contract (cron/CI friendly): 0 ok · 1 config error ·
2 fetch blocked · 3 drift unhealed (stale data served) · 4 schema
contract breach.
Declaring a source
stalin add writes this file — or write it yourself and let stalin compile it:
# sources/stories.yml — the INTENT. Hand-editable, never touched by the healer.
name: stories
url: https://news.ycombinator.com
schedule: 15m
item: each story row on the front page # natural language!
fields:
title:
type: str
desc: the headline text of each story
points:
type: int | null
desc: the upvote count; job postings have none
url:
type: url
desc: the link the headline points to
contract:
version: 1.0.0
min_items: 20 # fewer than this trips the drift alarmThe compiled selectors live in .stalin/lock.json — machine-owned, committed,
reviewed in PRs like a lockfile. You own the what; stalin owns the how.
This separation is the whole trick: the healer can rewrite selectors forever
without ever dirtying a file you edit.
Types
str · int · float · bool · url (resolved absolute) · datetime
(ISO-8601 out) · list[str] · enum[a,b,c] — all nullable via | null.
Query it 🔎 new in 0.3
Every source is now a queryable API — filter, sort, select fields, paginate,
and full-text search over the extracted items. Same grammar on HTTP, the MCP
tools, and the CLI. No more piping everything through jq.
# 3 love quotes NOT by Marilyn Monroe, sorted by author, trimmed payload
$ curl "localhost:8411/v1/quotes?tag=love&author__ne=Marilyn%20Monroe&sort=author&fields=text,author&limit=3"
{
"count": 7, // total matching the filters (before limit)
"returned": 3, // how many came back
"items": [ {"author": "André Gide", "text": "…"}, … ],
"_query": {"filters": {"author__ne": "Marilyn Monroe"},
"sort": "author", "fields": ["text","author"], "limit": 3, "offset": 0}
}Controls: sort=-points,author (- = desc) · fields=a,b (project) ·
limit / offset · q= (case-insensitive substring across text fields).
Filters are field (equality) or field__op:
op | meaning | op | meaning |
| equals / not |
|
|
| ordering (int/float/datetime) |
| substring, or list membership |
|
|
Filters are type-aware: points__gt=100 compares as an int, when__gte=2026-01-01
as a datetime. A bad value is a typed 400, never a 500:
{"error":"invalid_query","param":"points__gt","code":"invalid_value","expected_type":"int"}One rule where lookups and filters share a URL: for a live_lookup source, a
bare key that matches a declared param (?tag=love) drives the fetch; everything
else is a control or a filter. If a field happens to share a param's name, filter
it explicitly with field__eq=….
From the terminal — identical grammar:
stalin run quotes -p tag=love -w "author__ne=Marilyn Monroe" --sort author --fields text,author --limit 3For agents (MCP): get_data and every lookup_<source> tool take
filter (a {field__op: value} object), sort, fields, limit, offset,
and q. Each tool's description lists the source's filterable fields and types,
so a model can query precisely straight from get_schema — no scraping code,
no HTML in the prompt.
Self-healing is untouched: the query layer runs on already-typed items, downstream of extraction and healing.
Ask it in plain English 🗣️ new in 0.4
Don't want to learn the filter grammar? Ask. A local model compiles your question into a query and runs it through the exact engine from Query it — same filters, same types, same safety.
$ stalin ask quotes "3 love quotes not by Marilyn Monroe, just author and text"
✓ compiled → {'filters': {'author__ne': 'Marilyn Monroe'}, 'fields': ['author','text'], 'limit': 3}
✓ quotes 3/7 itemsGET /v1/quotes/ask?q=love%20quotes%20over%20100%20points%2C%20newest%20firstAnd as an MCP tool for agents — every source gets ask_<source>(question).
The LLM only proposes; the engine disposes. The model never sees the data
and never decides the answer — it emits a query in stalin's own grammar,
parse_query validates it against the schema (a bad guess is retried, not
served), and the deterministic engine runs it. Every response echoes the
compiled query in _query and the original in _meta.question, so you always
see exactly what it did — it can be incomplete, but never silently wrong.
Compilation quality tracks your local model: a small model (e.g. qwen3:1.7b)
handles clear questions well and occasionally drops a constraint; a larger one
is sharper. No Ollama, no ask — the structured query layer still works.
The API
stalin serve gives you versioned, contract-stable endpoints over cached
snapshots (your consumers never wait on a fetch, and target sites never sit
in your request path):
GET /v1/stories → {source, fetched_at, schema_version, stale, count, items[]}
GET /v1/stories/schema → JSON Schema for the items
POST /v1/stories/refresh → 202, background re-run (rate-limit guarded)
GET /openapi.json → OpenAPI 3.1 for everything
GET /healthz → per-source status: verified/healed/stale/brokenHealed-but-unconfirmed data is honestly labeled: "_meta": {"healed": true, "healed_fields": [...]}. Stale last-good data says "stale": true. There is
no propaganda in the payload.
MCP: feed your agents
stalin mcp # stdio server: list_sources, get_data, get_schemaPoint Claude Code (or any MCP client) at it and your agent gets typed,
self-healing website data as tools. Add to .mcp.json:
{"mcpServers": {"stalin": {"command": "stalin", "args": ["mcp"]}}}The LLM is optional
No Ollama? stalin still compiles most pages (the heuristic engine reads DOM
statistics, not tea leaves) and still detects every drift — it just can't run
rung 3, so a heal that fallbacks + heuristics can't solve exits 3 and tells
you to fix it. With Ollama, any model works: the protocol is
plain text with a sentinel line, not tool-calling — a 1.7B model on a potato
laptop heals real drift in under a minute, because the gates do the thinking.
Politeness doctrine
For a tool with this name, it is suspiciously well-behaved:
robots.txt respected by default. Overriding is per-source, explicit, and nags you on every single run.
Rate-limited (1 req / 2 s per host, jittered) with
Retry-Afterhonored and exponential backoff.Honest User-Agent — no browser impersonation in the default engine, ever.
The fetch classifier never heals against a block page. A 403, a Cloudflare challenge, a login redirect — those are fetch problems, not drift. stalin serves last-good data and says so, instead of learning to extract garbage from an "Access Denied" page.
No auth flows, no CAPTCHA anything, no paywalls. Hard line.
vs. the alternatives
stalin | Firecrawl | Crawl4AI | hand-rolled BS4 | |
Survives site redesigns | yes, automatically, verified | no | no | you, at 2am |
Typed schema contract | semver'd, validated every run | markdown out | markdown out | whatever you wrote |
Detects silent breakage | 5 signals, every run | – | – | – |
Works fully offline/local | yes (BYO Ollama or none) | cloud credits | yes | yes |
Serves an API + OpenAPI | built in | cloud | – | – |
Parameterized lookup API ( | built in | – | – | you write it |
MCP server | built in | cloud | yes | – |
Cost per 10k pages | $0 | ~$8–83 | $0 | your weekend |
Different tools for different jobs: Firecrawl/Crawl4AI turn pages into LLM-food (markdown). stalin turns pages into production data APIs with a stability guarantee. If your scraper feeds a dashboard, a pipeline, or a product — that guarantee is the product.
Architecture (for the curious)
stalin/
├── heuristics.py candidate proposers: DOM statistics, no LLM (the workhorse)
├── gates.py the five acceptance gates (the judge)
├── heal.py the 4-rung ladder (the crown jewel)
├── drift.py 5 cheap signals, microseconds, every run
├── fingerprint.py value shapes, node signatures, EMA baselines
├── compilepipe.py `add`: NL descriptions → verified selectors
├── engine.py fetch + politeness + the block-page classifier
├── extract.py selector execution + typed casting
├── schema.py the type system + pydantic + JSON Schema + semver
├── lockfile.py .stalin/lock.json (machine-owned, git-committed)
├── runner.py orchestration: fetch→classify→extract→drift→heal→emit
├── serve.py hand-rolled ASGI app (uvicorn), OpenAPI 3.1
├── mcp_server.py MCP over stdio
└── cli.py typer + rich (the propaganda department)Design lineage, honestly credited: the proposers-vs-judge split is borrowed
from karpathy/llm-council — many
cheap opinions, one deterministic verdict — and the sentinel text protocol
(instead of brittle structured tool-calls) is why a 1.7B local model is
enough. Small models can't fill out forms reliably, but they can end a
sentence with SELECTOR: span.karma.
Roadmap
Live parameterized lookups (
{param}URLs →?q=…APIs) — 0.2Parameterized MCP tools (
lookup_<source>(param=…)) — 0.2Queryable results — filter/sort/fields/paginate/search on every surface — 0.3
ask_<source>("plain-English question")— NL → the query engine, on every surface — 0.4change_watchmode — poll a page, emit a typed webhook on changeaggregatemode — one schema joined across N sites (entity resolution)batchmode — POST many inputs, get a typed array backJS rendering engine plugin (playwright/scrapling — the seam already exists)
Pagination (
next:selector +max_pages)Item-selector healing (fields heal; the container selector doesn't yet)
Contributing
Issues and PRs welcome. The bar for a heal-logic change: it must keep every
gate deterministic. The bar for a new engine: implement fetch(), nothing
else. The bar for README jokes: they must be about scrapers, not history.
License
MIT. Free as in "the collective owns the means of extraction."
This server cannot be deployed
Maintenance
Related MCP Connectors
Turn any website into structured JSON data matching your custom schema.
One MCP server for 180+ live web-data APIs returning clean JSON from sites that block scrapers.
One MCP for the Web. Easily search, crawl, navigate, and extract websites without getting blocked.…
APIs and MCP for structured public data, web research, CAPTCHA, and source-bound data cleanup.
Related MCP Servers
- FlicenseNot gradedqualityCmaintenanceTurns any website into a rich set of MCP tools for scraping, crawling, structured data extraction, and automatic API mounting via OpenAPI specs.-
- AlicenseCqualityCmaintenanceProvides browser automation and web scraping as MCP tools, enabling autonomous URL ingestion, crawling, extraction, and anti-bot handling with interactive browser control.625MIT
- FlicenseBqualityCmaintenanceCompiles any website into typed, callable tools for AI agents, enabling discovery and invocation of live web APIs and UI actions without custom MCP servers.81-
- FlicenseNot gradedqualityBmaintenanceSelf-hosted, cookie-aware web-automation engine that turns any website into callable MCP tools, with stateful browser sessions, web search, and multi-page crawling.-