Scraper Health
БесплатноНе проверенEnables autonomous self-healing scraper fleet management for Bright Data Scraper Studio, with health checking, anomaly detection, and automated AI-driven scrape
Описание
Enables autonomous self-healing scraper fleet management for Bright Data Scraper Studio, with health checking, anomaly detection, and automated AI-driven scraper repair and approval.
README
Autonomous Self-Healing Scraper Fleet Manager for Bright Data Scraper Studio
The first agent that closes Bright Data's self-healing loop end-to-end without a human in the middle — turning the
resume_automation_jobendpoint the official demo couldn't find into a one-command "deploy and forget" scraper fleet.
Built for WeMakeDevs Into the Scrape-Verse hackathon (Aug 17–23, 2026).
🎯 The Problem
Web scrapers break silently. When a target site renames a CSS class, moves a field, or redesigns a layout, traditional scrapers return empty/garbage rows with no alarm. The failure is discovered only when a human notices the data is wrong — by which point downstream systems have been consuming bad data for hours or days.
✅ The Solution
Scraper-Health-MCP is an autonomous AI agent that wraps Bright Data's Scraper Studio self-healing API into a fully automated loop:
- Monitor — Runs scrapers on schedule and health-checks every result
- Detect — Catches breakage via schema validation, null-field detection, and row-count anomaly detection (Sentinel-style statistical baselines)
- Heal — Triggers Bright Data's AI self-healing (
refactor_template) - Auto-Approve — Programmatically accepts the AI's proposed extraction diff via
resume_automation_job(the step Bright Data's own demo couldn't do) - Verify — Re-scrapes and confirms health is restored
- Escalate — If healing fails, regenerates the scraper from scratch
🔑 The Technical Unlock
Bright Data's official self-healing demo repo (anil-bd/scraper-studio-self-healing-demo) explicitly states the public API "does not document an endpoint to approve programmatically" and exits with code 3 (awaiting approval) when the heal hits pending_answer, requiring manual UI approval.
The current docs DO expose POST /resume_automation_job with {message: true, auto_save: true} to accept the diff automatically. This means a fully autonomous, hands-off self-healing loop is now buildable — and almost no competitor will have found this.
🤖 MCP Server
The agent exposes 5 MCP tools callable from Claude Code, Cursor, or any MCP-compatible AI agent:
| Tool | Description |
|---|---|
create_scraper |
Create a new scraper from URL + description via Bright Data AI Flow |
run_collector |
Trigger a collector and return results |
health_check |
Run collector + check output health (schema, nulls, row-count anomaly) |
self_heal |
Full autonomous loop: detect → heal → auto-approve → re-scrape → verify |
verify |
Verify a healed collector has restored health |
🏗️ Architecture
Register collector (ID + schema + required fields)
│
▼
Schedule / trigger run ──► POST /dca/trigger
│
▼
Health-check result ──► GET /dca/dataset (schema drift? nulls? row-count anomaly?)
│
├── healthy ─► log success, schedule next run
└── broken ─► TRIGGER SELF-HEAL
│
▼
POST /refactor_template (targeted heal prompt from the failed field)
│
▼
Poll /refactor_template/progress
│
├── status:"pending_answer" ─► POST /resume_automation_job
│ {message:true, auto_save:true} ← the unlock
└── done/failed
│
▼
Re-scrape + verify against baseline schema
│
├── passes ─► log heal event, resume schedule
└── fails ─► escalate: regenerate scraper from scratch (Workflow 1)
+ alert/notification
🛠️ Tech Stack
| Layer | Tech |
|---|---|
| Scraper infra | Bright Data Scraper Studio (CLI + AI Flow API) |
| Backend | Python 3.12 + FastAPI |
| Agent interface | MCP server (5 tools) |
| Anomaly detection | In-package stats (mean/std row-count + schema validator) |
| Dashboard | Jinja2 templates + dark-themed HTML/CSS/JS |
| Deploy | Vercel serverless (free tier) |
| Repo | github.com/0xConsole/scraper-health-mcp |
🚀 Setup
# Clone
git clone https://github.com/0xConsole/scraper-health-mcp.git
cd scraper-health-mcp
# Install
pip install -r requirements.txt
# Run (mock mode — no API key needed)
python -m uvicorn app.main:app --reload
# Run (live mode — with Bright Data API key)
export BRIGHTDATA_API_KEY="your-key-here"
python -m uvicorn app.main:app --reload
Open http://localhost:8000 to see the dashboard.
📡 API Endpoints
| Method | Path | Description |
|---|---|---|
| GET | / |
Dashboard |
| GET | /api/health |
Health check |
| GET | /api/status |
Full orchestrator status |
| GET | /api/tools |
List MCP tools |
| GET | /api/mcp/manifest |
MCP server manifest |
| POST | /api/create_scraper |
Create scraper (MCP tool 1) |
| POST | /api/run_collector |
Run collector (MCP tool 2) |
| POST | /api/health_check |
Health check (MCP tool 3) |
| POST | /api/self_heal |
Self-heal loop (MCP tool 4) |
| POST | /api/verify |
Verify heal (MCP tool 5) |
| POST | /api/demo |
Full demo (break + heal cycle) |
| POST | /api/trigger_breakage |
Simulate breakage + trigger heal |
🎪 Demo
- Click "Run Full Demo" on the dashboard
- The agent health-checks all registered collectors
- Simulates a site change (breakage) on the first collector
- Detects the breakage via health check (null fields, row count anomaly)
- Triggers AI self-healing (
refactor_template) - Polls until the AI proposes a diff (
pending_answer) - Auto-approves the diff via
resume_automation_job← the unlock - Re-scrapes and verifies health is restored
- Logs the entire heal event in the timeline
📊 What's Real vs Mocked
| Component | Status |
|---|---|
| MCP server (5 tools) | ✅ Real — fully functional |
| Health checker (schema, nulls, anomaly) | ✅ Real — Sentinel-style stats |
| Heal orchestrator (full loop) | ✅ Real — all states wired |
Auto-approve (resume_automation_job) |
✅ Real — calls actual endpoint when API key set |
| Bright Data API calls | 🔧 Mock mode (no key) / Real (with key) |
| Demo collectors | ✅ 3 seeded (HN, e-commerce, docs) |
| Dashboard + heal timeline | ✅ Real — live data from orchestrator |
📝 License
Apache 2.0
🔗 Links
- Live demo: https://scraper-health-mcp.vercel.app
- GitHub: https://github.com/0xConsole/scraper-health-mcp
- Hackathon: WeMakeDevs Into the Scrape-Verse (Aug 17–23, 2026)
- Bright Data Scraper Studio: https://brightdata.com/scraper-studio
Built by Sentinel Dev · Team: Xayaan Ibrahim (Individual)
Установка Scraper Health
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/0xConsole/scraper-health-mcpFAQ
Scraper Health MCP бесплатный?
Да, Scraper Health MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Scraper Health?
Нет, Scraper Health работает без API-ключей и переменных окружения.
Scraper Health — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Scraper Health в Claude Desktop, Claude Code или Cursor?
Открой Scraper Health на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
Похожие MCP
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
автор: xuzexin-hzMCP-Agent
A simple, composable framework to build agents using Model Context Protocol by [LastMile AI](https://www.lastmileai.dev)
автор: lastmile-aiSpring AI MCP Client
Provides auto-configuration for MCP client functionality in Spring Boot applications.
mcp.natoma.ai
A Hosted MCP Platform to discover, install, manage and deploy MCP servers by [Natoma Labs](https://www.natoma.ai)
MCPHub
Website to list high quality MCP servers and reviews by real users. Also provide online chatbot for popular LLM models with MCP server support.
MCP Servers Rating and User Reviews
Website to rate MCP servers, write authentic user reviews, and [search engine for agent & mcp](http://www.deepnlp.org/search/agent)
mkinf
An Open Source registry of hosted MCP Servers to accelerate AI agent workflows.
Compare Scraper Health with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории ai
