openai-websearch-mcp

This MCP server provides access to OpenAI's websearch functionality through the Model Context Protocol. It allows AI assistants to search the web during conversations with users, providing up-to-date information that may not be available in the assistant's training data. The server can be installed and configured for use with Claude.app or Zed editor.

One click installation & Configuration

Claude

!!Can using this command auto update configure file（Recommend）

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

sk-xxxx is your API key. You can get it from openai's open platform

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Windsurf

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Available Tools

• web_search - Call openai websearch as tool.
  • Required arguments:
    • type (string): web_search_preview
    • search_context_size (string): High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.
    • user_location (object or null)
      • type (string): The type of location > approximation. Always approximate.
      • city (string): Free text input for the city of the user, e.g. San Francisco.
      • country (string): The two-letter ISO country code of the user, e.g. US.
      • region (string): Free text input for the region of the user, e.g. California.
      • timezone (string): The IANA timezone of the user, e.g. America/Los_Angeles.

Manual installation and configuration

Please make sure uvx is installed before installation

Add to your Claude settings:

1、Using uvx

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

2、Using pip installation

1）install openai-websearch-mcp via pip:

pip install openai-websearch-mcp

2）modify your Claude settings

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

Configure for Zed

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. For uvx installations:

npx @modelcontextprotocol/inspector uvx openai-websearch-mcp