ConechoAI/openai-websearch-mcp

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.
✨ Features
- **🧠 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
🚀 Quick Start
One-Click Installation for Claude Desktop
Replace sk-xxxx with your OpenAI API key from the OpenAI Platform.
⚙️ Configuration
Claude Desktop
Add to your claude_desktop_config.json:
Cursor
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:
Claude Code
Claude Code automatically detects MCP servers configured for Claude Desktop. Use the same configuration as above for Claude Desktop.
Local Development
For local testing, use the absolute path to your virtual environment:
🛠️ Available Tools
openai_web_search
Intelligent web search with reasoning model support.
Parameters
| Parameter | Type | Description | Default |
|-----------|------|-------------|---------|
| input | string | The search query or question to search for | *Required* |
| model | string | AI model to use. Supports gpt-4o, gpt-4o-mini, gpt-5, gpt-5-mini, gpt-5-nano, o3, o4-mini | gpt-5-mini |
| reasoning_effort | string | Reasoning effort level: low, medium, high, minimal | Smart default |
| type | string | Web search API version | web_search_preview |
| search_context_size | string | Context amount: low, medium, high | medium |
| user_location | object | Optional location for localized results | null |
💬 Usage Examples
Once configured, simply ask your AI assistant to search for information using natural language:
Quick Search
> "Search for the latest developments in AI reasoning models using openai_web_search"
Deep Research
> "Use openai_web_search with gpt-5 and high reasoning effort to provide a comprehensive analysis of quantum computing breakthroughs"
Localized Search
> "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.
🤖 Model Selection Guide
Quick Multi-Round Searches 🚀
- **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
Deep Research 🔬
- **Recommended**: gpt-5 with reasoning_effort: "medium" or "high"