Fieldwright
Fieldwright: web page to clean Markdown, metadata, JSON-LD, emails, phones.
我該用這個嗎
品質與安全性
A
根據工具定義與協定合規性的自動化分析。
上下文成本
~187Token(工具定義)
~825 B典型回應大小
極小的注意力影響(128k 上下文的 0.15%)
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案:
{
"mcpServers": {
"ai-extract": {
"url": "https://fieldwright.cybermax-tools.workers.dev/mcp"
}
}
}遠端端點
https://fieldwright.cybermax-tools.workers.dev/mcpstreamable-http它能做什麼
工具清單
工具(1)
🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢extract_page(url, max_chars, include_markdown)
Fetch one public web page and return its readable content as compact Markdown (links and tables kept) plus title, meta description, language, canonical URL, OpenGraph/Twitter tags, JSON-LD structured data (products, articles, organisations, events), mailto emails and tel phone numbers. Use to read or summarise a page or pull its schema.org data. No JavaScript rendering.
輸入結構描述
{
"type": "object",
"properties": {
"url": {
"type": "string",
"description": "Public http(s) URL"
},
"max_chars": {
"type": "integer",
"minimum": 500,
"maximum": 20000,
"default": 8000,
"description": "Markdown length cap"
},
"include_markdown": {
"type": "boolean",
"default": true
}
},
"required": [
"url"
]
}社群
證據
近期觀測
已驗證未記錄版本1 個工具