OpenAI WebSearch
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
Jump to
- 🧠 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:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
OpenAI WebSearchCommand (node, npx, python, etc.)uvxArguments-
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.
-
Argument 1
- 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 🔍
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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