What does the server do?
It exposes a `web_search` tool that uses OpenAI’s Responses API to perform live web searches, returning results directly to an MCP client.
@bitibi
Basic information
A server for handling OpenAI web search using MCP (Multi-Config Protocol)
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"OpenAI-WebSearch-MCP-Server": {
"command": "npx",
"args": [
"openai-websearch-mcp-server"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
A TypeScript‑based MCP server that lets AI models perform real‑time web searches through the OpenAI API, using the Responses API’s web_search_preview feature. It is built for developers who want to add live web search capabilities to any MCP‑compatible client (e.g., Claude Desktop).
Install with npx openai-websearch-mcp-server or npm install -g openai-websearch-mcp-server, then set the OPENAI_API_KEY environment variable. Run the server with openai-websearch-mcp. Configure your MCP client to launch the server and send tool calls to the web_search tool, which accepts a query string and returns results from across the internet.
web_search_preview capabilityweb_search)npx or install globallyPORT environment variableIt exposes a `web_search` tool that uses OpenAI’s Responses API to perform live web searches, returning results directly to an MCP client.
Set the environment variable `OPENAI_API_KEY` before running the server: `export OPENAI_API_KEY='your-api-key-here'`.
Only an OpenAI API key with access to the Responses API’s `web_search_preview` feature. No additional database or third‑party search engine is required.
Set the `PORT` environment variable, e.g., `PORT=8080 openai-websearch-mcp`. The default port is 3000.
It is designed to be launched by an MCP client (like Claude Desktop) via the command line, with the API key provided in the client configuration’s environment.

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