ZenRows MCP Server

The ZenRows MCP (Model Context Protocol) server is the standard way AI systems use ZenRows. A single connection gives your AI assistant, agent, or application real-time access to any website.

📚 Full documentation: docs.zenrows.com/integrations/mcp/mcp-overview

Why ZenRows MCP

• Reach sites that normally block bots. Get access to any website at scale without getting blocked by anti-bot systems.
• Managed scraping infrastructure. Proxy rotation, headless browser orchestration, anti-bot evasion, and session management run on ZenRows infrastructure.
• Plug into any AI you already use. Works with any MCP client, including AI assistants, agent frameworks, AI SDKs, IDE plugins, and custom applications.
• Plain English, no scraping code. Describe the task naturally and the AI picks the right tool. No selectors, no proxy management, no anti-bot tuning.

Quick start

ZenRows MCP supports two transport options. Both expose the same set of tools and capabilities. Pick the one that fits your client.

Remote MCP server

Use the hosted ZenRows MCP server when your AI application calls an LLM API directly. The server runs on ZenRows infrastructure, so there is nothing to install, configure, or update.

Server URL:

https://mcp.zenrows.com/mcp

Transport: Streamable HTTP

Authentication: OAuth-based. Pass your ZenRows API key as a Bearer token in the Authorization header on every request.

Authorization: Bearer YOUR_ZENROWS_API_KEY

Most MCP clients accept this through an authorization shorthand field on the tool config and forward it as the Bearer token automatically. Some clients use a free-form headers field instead. Either approach works.

Example: OpenAI Responses API

import os
from openai import OpenAI

ZENROWS_API_KEY = os.environ["ZENROWS_API_KEY"]
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

response = client.responses.create(
    model="gpt-5",
    tools=[
        {
            "type": "mcp",
            "server_label": "zenrows",
            "server_description": "Web scraping MCP server for accessing live web content.",
            "server_url": "https://mcp.zenrows.com/mcp",
            "authorization": ZENROWS_API_KEY,
            "require_approval": "never",
        }
    ],
    input="Visit https://news.ycombinator.com/ and summarize the three most recent posts.",
)

print(response.output_text)

For the full walkthrough with framework-specific examples, see the Remote MCP server docs.

Local MCP server

Use the local stdio configuration when your MCP client runs the server as a local subprocess instead of calling a remote URL. This is the standard setup for desktop AI tools and IDE plugins, including Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, Zed, and JetBrains IDEs.

Package: @zenrows/mcp on npm

Authentication: API key via the ZENROWS_API_KEY environment variable.

Requirements: Node.js installed (for npx to work).

Configuration:

{
  "mcpServers": {
    "zenrows": {
      "command": "npx",
      "args": ["-y", "@zenrows/mcp"],
      "env": {
        "ZENROWS_API_KEY": "YOUR_ZENROWS_API_KEY"
      }
    }
  }
}

The exact location of this config varies by client. See the [per-client setup guides](https://docs.zenrows.com/inte

... View full README on GitHub