OpenAI WebSearch MCP Server 🔍

An advanced MCP server that provides intelligent web search capabilities using OpenAI's reasoning models. Perfect for AI assistants that need up-to-date information with smart reasoning capabilities.

• 🧠 Reasoning Model Support: Full compatibility with OpenAI's latest reasoning models (gpt-5, gpt-5-mini, gpt-5-nano, o3, o4-mini)
• ⚡ Smart Effort Control: Intelligent reasoning_effort defaults based on use case
• 🔄 Multi-Mode Search: Fast iterations with gpt-5-mini or deep research with gpt-5
• 🌍 Localized Results: Support for location-based search customization
• 📝 Rich Descriptions: Complete parameter documentation for easy integration
• 🔧 Flexible Configuration: Environment variable support for easy deployment

OPENAI_API_KEY=sk-xxxx uvx --with openai-websearch-mcp openai-websearch-mcp-install

Replace sk-xxxx with your OpenAI API key from the OpenAI Platform.

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "openai-websearch-mcp": {
      "command": "uvx",
      "args": ["openai-websearch-mcp"],
      "env": {
        "OPENAI_API_KEY": "your-api-key-here",
        "OPENAI_DEFAULT_MODEL": "gpt-5-mini"
      }
    }
  }
}

Add to your MCP settings in Cursor:

1. Open Cursor Settings (Cmd/Ctrl + ,)
2. Search for "MCP" or go to Extensions → MCP
3. Add server configuration:

{
  "mcpServers": {
    "openai-websearch-mcp": {
      "command": "uvx",
      "args": ["openai-websearch-mcp"],
      "env": {
        "OPENAI_API_KEY": "your-api-key-here",
        "OPENAI_DEFAULT_MODEL": "gpt-5-mini"
      }
    }
  }
}

Claude Code automatically detects MCP servers configured for Claude Desktop. Use the same configuration as above for Claude Desktop.

For local testing, use the absolute path to your virtual environment:

{
  "mcpServers": {
    "openai-websearch-mcp": {
      "command": "/path/to/your/project/.venv/bin/python",
      "args": ["-m", "openai_websearch_mcp"],
      "env": {
        "OPENAI_API_KEY": "your-api-key-here",
        "OPENAI_DEFAULT_MODEL": "gpt-5-mini",
        "PYTHONPATH": "/path/to/your/project/src"
      }
    }
  }
}

Intelligent web search with reasoning model support.

Once configured, simply ask your AI assistant to search for information using natural language:

"Search for the latest developments in AI reasoning models using openai_web_search"

"Use openai_web_search with gpt-5 and high reasoning effort to provide a comprehensive analysis of quantum computing breakthroughs"

"Search for local tech meetups in San Francisco this week using openai_web_search"

The AI assistant will automatically use the openai_web_search tool with appropriate parameters based on your request.

• Recommended: gpt-5-mini with reasoning_effort: "low"
• Use Case: Fast iterations, real-time information, multiple quick queries
• Benefits: Lower latency, cost-effective for frequent searches

• Recommended: gpt-5 with reasoning_effort: "medium" or "high"
• Use Case: Comprehensive analysis, complex topics, detailed investigation
• Benefits: Multi-round reasoned results, no need for agent iterations

# Install and run directly
uvx openai-websearch-mcp

# Or install globally
uvx install openai-websearch-mcp

# Install from PyPI
pip install openai-websearch-mcp

# Run the server
python -m openai_websearch_mcp

# Clone the repository
git clone https://github.com/yourusername/openai-websearch-mcp.git
cd openai-websearch-mcp

# Install dependencies
uv sync

# Run in development mode
uv run python -m openai_websearch_mcp

# Clone and setup
git clone https://github.com/yourusername/openai-websearch-mcp.git
cd openai-websearch-mcp

# Create virtual environment and install dependencies
uv sync

# Run tests
uv run python -m pytest

# Install in development mode
uv pip install -e .

# For uvx installations
npx @modelcontextprotocol/inspector uvx openai-websearch-mcp

# For pip installations
npx @modelcontextprotocol/inspector python -m openai_websearch_mcp

Issue: "Unsupported parameter: 'reasoning.effort'" Solution: This occurs when using non-reasoning models (gpt-4o, gpt-4o-mini) with reasoning_effort parameter. The server automatically handles this by only applying reasoning parameters to compatible models.

Issue: "No module named 'openai_websearch_mcp'" Solution: Ensure you've installed the package correctly and your Python path includes the package location.

This project is licensed under the MIT License - see the LICENSE file for details.

• 🤖 Generated with Claude Code
• 🔥 Powered by OpenAI's Web Search API
• 🛠️ Built on the Model Context Protocol

Co-Authored-By: Claude noreply@anthropic.com