OpenAI WebSearch MCP Server

SearchPython

Access OpenAI's web search functionality through MCP

Available Tools

web_search

Call OpenAI websearch to retrieve up-to-date information from the web

typesearch_context_sizeuser_location

OpenAI WebSearch MCP provides access to OpenAI's web search functionality through the Model Context Protocol. It allows AI assistants to search the web during conversations, providing up-to-date information that may not be available in the assistant's training data. This MCP server acts as a bridge between AI assistants and the OpenAI API, enabling real-time web search capabilities. It can be easily configured for use with Claude.app, Zed editor, and other MCP-compatible clients.

Installation

There are two main ways to install the OpenAI WebSearch MCP:

Option 1: One-click Installation (Recommended)

This method automatically installs and configures the MCP server:

OPENAI_API_KEY=sk-xxxx uv run --with uv --with openai-websearch-mcp openai-websearch-mcp-install

Replace sk-xxxx with your OpenAI API key, which you can obtain from the OpenAI platform.

Option 2: Manual Installation

Prerequisites

Make sure uvx is installed on your system

Installation Steps

Install the package using pip:
```
pip install openai-websearch-mcp
```
Configure your AI client settings as shown in the configuration section below.

Configuration

For Claude

Add the following to your Claude settings:

Using uvx:

"mcpServers": {
  "openai-websearch-mcp": {
    "command": "uvx",
    "args": ["openai-websearch-mcp"],
    "env": {
        "OPENAI_API_KEY": "your-api-key-here"
    }
  }
}

Using pip installation:

"mcpServers": {
  "openai-websearch-mcp": {
    "command": "python",
    "args": ["-m", "openai_websearch_mcp"],
    "env": {
        "OPENAI_API_KEY": "your-api-key-here"
    }
  }
}

For Zed Editor

Add to your Zed settings.json:

Using uvx:

"context_servers": [
  "openai-websearch-mcp": {
    "command": "uvx",
    "args": ["openai-websearch-mcp"],
    "env": {
        "OPENAI_API_KEY": "your-api-key-here"
    }
  }
],

Using pip installation:

"context_servers": {
  "openai-websearch-mcp": {
    "command": "python",
    "args": ["-m", "openai_websearch_mcp"],
    "env": {
        "OPENAI_API_KEY": "your-api-key-here"
    }
  }
},

Debugging

You can use the MCP inspector to debug the server:

npx @modelcontextprotocol/inspector uvx openai-websearch-mcp

This will help you identify any issues with the MCP server configuration or operation.