Keiro: A Cost-Effective Search and Web Crawling API Service for AI Intelligentsia

Keiro Labs is a web search and data crawling API service designed for Artificial Intelligence (AI) and Large Language Model (LLM) applications. Its core goal is to address the high cost and format confusion that AI Agents currently face when accessing real-time web data. Compared to traditional search engine APIs, Keiro Labs focuses on providing “machine-friendly” data by automatically removing web advertisements and redundant code, and returning cleaned Markdown-formatted text, which greatly reduces the need for LLM. token Consumption.

The platform is particularly well suited for developers building RAG (Retrieval Augmented Generation) systems, AI chatbots, and automated research assistants.Keiro Labs achieves a far lower cost of ownership than competing products in the market (such as the Tavily or Exa) prices. In addition, it natively supports MCP (Model Context Protocol), which lets Claude 或 ChatGPT Advanced models, such as the AI model, can directly invoke its search capabilities, making it a “data fuel” supply station for developers to build production-grade AI apps.

Function List

• Intelligent Web Search API: Provided /search endpoints, supports real-time networked search, and returns refined search results optimized for LLM.
• deep web crawler: By /crawl It is capable of bypassing anti-crawler mechanisms, extracting the full content of any web page and converting it to a clean Markdown format.
• RAG Contextual Memory: Provides unlimited contextual memory endpoints, automatically updating and storing request responses to support a persistent knowledge base for AI.
• Intelligent Routing SystemThe API is designed to automatically recognize simple queries and complex research tasks, dynamically allocate computing resources, and significantly reduce the cost of API calls while ensuring quality.
• MCP Server Support: the official Node.js and Python versions of the MCP servers, supporting one-click integration into Claude Desktop or LobeChat among other AI clients.
• Asynchronous Task Queue: Supports highly concurrent asynchronous request processing, which is suitable for AI intelligences to perform background research tasks in batch, without having to wait for a long time for synchronized responses.

Using Help

Keiro Labs is very intuitive for developers to use, interacting primarily through standard REST APIs, while also providing an MCP integration solution for non-code users.

1. Get the API key

First, you need to visit the keirolabs.cloud Register for an account. New users are usually given free usage credits (e.g. 500 requests) for testing. After logging into the console, in the Dashboard generate your API Key。

2. Search via API (Python example)

This is the most basic usage and is suitable for integration into your Python backend services.

import requests
url = "https://api.keirolabs.cloud/v1/search"
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
payload = {
"query": "2026年最新的AI智能体开发框架有哪些？",
"depth": "basic",  # 可选 'deep' 进行更深入研究
"include_markdown": True
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())

The returned data will contain cleaned web page summaries and Markdown content that you can feed directly to GPT-4 or Claude.

3. Integration into Claude Desktop (MCP Usage)

If you are using the desktop version of Claude's application, you can configure the MCP server to give Claude networked search capabilities directly, without writing code.

Installation Steps:

1. Ensure that your computer has a Node.js environment installed.
2. Clone the official repository (in the case of the Node version):

   git clone https://github.com/keiro-labs/keiro-mcp.git
   cd keiro-mcp
   npm install
   npm run build
   

3. Modify Claude's configuration file (usually located in the %APPDATA%\Claude\claude_desktop_config.json or Mac ~/Library/Application Support/Claude/）：

   {
   "mcpServers": {
   "keiro": {
   "command": "node",
   "args": ["/绝对路径/到/keiro-mcp/dist/index.js"],
   "env": {
   "KEIRO_API_KEY": "你的_API_KEY"
   }
   }
   }
   }
   

4. Restart Claude Desktop. you'll notice an additional tool icon near the input box, and now you can ask Claude directly: “Search for the latest price of Keiro Labs for me” and it will automatically call the API and answer.

4. Data capture and cleansing

For scenarios where you need to read the content of a specific web page, use the /crawl Endpoints:
Send a message containing url The system automatically handles the JavaScript rendering and back-crawl validation of the POST request, returning clean text. This is useful for building a domain-specific knowledge base.

application scenario

1. Building Industry Instant Intelligence Bots
   Developers can use Keiro Labs“ search API to monitor industry-specific keywords (e.g., ”semiconductor price change") on a regular basis, automatically grabbing the latest news and generating a daily report to send to the team.
2. RAG Knowledge Base Automation
   When enterprises build internal Q&A systems, they can use the crawling function to batch process the target websites (e.g., competing documents, technical blogs), and store the cleaned Markdown data into the vector database to greatly improve the retrieval accuracy.
3. Academic research and dissertation assistance
   By integrating Keiro's AI assistant, researchers can give the command “Find all key papers on multimodal modeling in the last three years” in one go, and the system automatically performs deep searches and abstracts, saving a lot of time on literature searches.

QA

1. What is the difference between Keiro Labs and Tavily or Exa?
   The core difference is(manufacturing, production etc) costs和specificationKeiro Labs optimizes the price for high-frequency calls to the AI Agent (about 20%-30% of the competition) and returns a minimalist Markdown format by default, saving the LLM's context window even more.
2. Can it crawl sites that require a login?
   Typically, Keiro Labs focuses on public web data. It handles well for pages rendered via a simple cookie wall or dynamically (e.g., SPA one-page apps), but may be limited for content behind a strict paywall.
3. What is MCP Support and why is it important?
   MCP (Model Context Protocol) is a new standard that allows AI models to connect directly to external tools, and Keiro's native support for MCP means that you don't need to write your own “glue code” to allow models like Claude to use Keiro's search capabilities directly, out of the box. out-of-the-box.