OpenAI WebSearch

by conechoai

40 stars
29k downloads
Not rated
GitHub

About

Enables AI assistants to search the web in real-time through OpenAI's websearch functionality, retrieving up-to-date information beyond training data cutoffs with configurable search parameters.

Details

Author
conechoai
Repository
ConechoAI/openai-websearch-mcp
GitHub stars
40
Downloads
28,957
License
MIT License
Categories
Search, Other, AI, Developer Tools, Infrastructure, Knowledge Base
Tags
#web, #web-research, #openai

- 🧠 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

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name OpenAI WebSearch
    Command (node, npx, python, etc.) uvx
    Arguments
    • Argument 1 openai-websearch-mcp
    Environment
    • OPENAI_API_KEY your-api-key-here
    • OPENAI_DEFAULT_MODEL gpt-5-mini

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

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.

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"

- 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

uvx openai-websearch-mcp

uvx install openai-websearch-mcp


pip install openai-websearch-mcp

uv sync

bash

git clone https://github.com/yourusername/openai-websearch-mcp.git
cd openai-websearch-mcp

uv sync

uv pip install -e .


| Variable | Description | Default |
|----------|-------------|---------|
| OPENAI_API_KEY | Your OpenAI API key | Required |
| OPENAI_DEFAULT_MODEL | Default model to use | gpt-5-mini |

npx @modelcontextprotocol/inspector uvx openai-websearch-mcp

npx @modelcontextprotocol/inspector python -m openai_websearch_mcp

openai_web_search

Intelligent web search with reasoning model support. Parameters: input (string, required), model (string, optional, default: gpt-5-mini), reasoning_effort (string, optional, smart default), type (string, optional, default: web_search_preview), search_context_size (string, optional, default: medium), user_location (object, optional, default: null).

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

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

Linux

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

Macos

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

Windows

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

OpenAI WebSearch MCP Server 🔍

PyPI version
Python 3.10+
MCP Compatible
License: MIT

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

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.

⚙️ Configuration

Claude Desktop

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"
      }
    }
  }
}

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:

{
  "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

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:

{
  "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"
      }
    }
  }
}

🛠️ 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" - Use Case: Comprehensive analysis, complex topics, detailed investigation - Benefits: Multi-round reasoned results, no need for agent iterations

Model Comparison

| Model | Reasoning | Default Effort | Best For |
|-------|-----------|----------------|----------|
| gpt-4o | ❌ | N/A | Standard search |
| gpt-4o-mini | ❌ | N/A | Basic queries |
| gpt-5-mini | ✅ | low | Fast iterations |
| gpt-5 | ✅ | medium | Deep research |
| gpt-5-nano | ✅ | medium | Balanced approach |
| o3 | ✅ | medium | Advanced reasoning |
| o4-mini | ✅ | medium | Efficient reasoning |

📦 Installation

Using uvx (Recommended)

```bash

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