SteadyFetch
Provides AI agents with reliable web fetching capabilities, handling retries, caching, and anti-bot bypass automatically.
README
<!-- mcp-name: io.github.carsonroell-debug/steadyfetch -->
SteadyFetch
Reliable web fetching for AI agents. Stop losing hours to Cloudflare blocks, timeouts, and flaky scrapes.
SteadyFetch is an MCP server that gives your AI agents reliable web access with automatic retry, circuit breaker protection, caching, and anti-bot bypass — out of the box.
The Problem
Every AI agent that touches the web hits the same wall:
- Cloudflare blocks your requests
- Sites return CAPTCHAs
- Pages timeout or load partially
- Rate limits kill your batch jobs
- You waste hours debugging flaky scrapes
The Solution
One MCP tool call. SteadyFetch handles the rest.
Agent calls fetch_url("https://example.com")
→ Checks cache (instant if hit)
→ Checks circuit breaker (fail-fast if domain is down)
→ Stealth browser fetch with anti-bot bypass
→ On failure: retry with exponential backoff
→ Fallback: plain HTTP fetch
→ Cache the result
→ Return clean markdown + raw HTML
Tools
| Tool | Description |
|---|---|
fetch_url |
Full reliability fetch — returns markdown + HTML |
fetch_markdown |
Returns only clean markdown, optimized for LLMs |
check_domain |
Circuit breaker status for a domain |
cache_stats |
Cache utilization metrics |
clear_cache |
Flush the cache for fresh data |
Quick Start
Install from PyPI
pip install steadyfetch
steadyfetch
Then connect from Claude Desktop:
{
"mcpServers": {
"steadyfetch": {
"command": "steadyfetch"
}
}
}
Self-host with Docker
docker build -t steadyfetch .
docker run -p 8200:8200 steadyfetch
Configuration
All settings via environment variables:
| Variable | Default | Description |
|---|---|---|
PORT |
8200 | Server port |
STEADYFETCH_MAX_RETRIES |
3 | Retry attempts per URL |
STEADYFETCH_CIRCUIT_THRESHOLD |
5 | Failures before circuit opens |
STEADYFETCH_CIRCUIT_COOLDOWN |
120 | Seconds before retrying a broken domain |
STEADYFETCH_CACHE_TTL |
3600 | Cache lifetime in seconds |
STEADYFETCH_TIMEOUT |
30000 | Page load timeout in ms |
How It Works
Retry with backoff — Exponential backoff + jitter prevents retry storms. 3 browser attempts before falling back to HTTP.
Circuit breaker — Per-domain failure tracking. After 5 consecutive failures, the domain is circuit-broken for 2 minutes. Prevents wasting time on sites that are blocking you.
Caching — Disk-backed cache with configurable TTL. Repeat fetches are instant. 500MB default limit.
Anti-bot bypass — Stealth browser with magic mode, navigator patching, and human-like behavior simulation via Crawl4AI.
Graceful degradation — If the browser can't get through, falls back to plain HTTP. If HTTP fails, returns a clear error with domain health status. Never hangs, never silently fails.
Free vs Pro
| Tool | Free | Pro ($19/mo) |
|---|---|---|
fetch_url |
Yes (no JS render, no cache) | Yes (full: JS render + cache + anti-bot) |
check_domain |
Yes | Yes |
fetch_markdown |
- | Yes |
cache_stats |
- | Yes |
clear_cache |
- | Yes |
Free tier gives you basic HTTP fetching and domain health checks. Pro unlocks JS rendering, anti-bot bypass, caching, and clean markdown output.
Upgrade to Pro on MCPize — $19/mo or $190/yr.
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。