工具 API

apify-slash-rag-web-browser

This tool calls the Actor "apify/rag-web-browser" and retrieves its output results. Use this tool instead of the "call-actor" if user requests this specific Actor. Actor description: Web browser for OpenAI Assistants, RAG pipelines, or AI agents, similar to a web browser in ChatGPT. It queries Google Search, scrapes the top N pages, and returns their content as Markdown for further processing by an LLM. It can also scrape individual URLs.Use this tool when user wants to GET or RETRIEVE actual data immediately (one-time data retrieval). This tool directly fetches and returns data - it does NOT just find tools. Examples of when to use: - User wants current/immediate data (e.g., "Get flight prices for tomorrow", "What's the weather today?") - User needs to fetch specific content now (e.g., "Fetch news articles from CNN", "Get product info from Amazon") - User has time indicators like "today", "current", "latest", "recent", "now" This is for general web scraping and immediate data needs. For repeated/scheduled scraping of specific platforms (e-commerce, social media), consider suggesting a specialized Actor from the Store for better performance and reliability.

creativeOAuth1 积分

调用信息

工具标识
apify-mcp-server.apify-slash-rag-web-browser
服务提供方
Apify
平均响应
5987 ms
近 7 天调用
1

输入参数

query必填

**REQUIRED** Enter Google Search keywords or a URL of a specific web page. The keywords might include the [advanced search operators](https://blog.apify.com/how-to-scrape-google-like-a-pro/). Examples: - <code>san francisco weather</code> - <code>https://www.cnn.com</code> - <code>function calling site:openai.com</code> Example values: "web browser for RAG pipelines -site:reddit.com"

maxResults

The maximum number of top organic Google Search results whose web pages will be extracted. If `query` is a URL, then this field is ignored and the Actor only fetches the specific web page. Example values: 3

outputFormats

Select one or more formats to which the target web pages will be extracted and saved in the resulting dataset. Example values: ["markdown"]