Skip to main content
Glama
luchiniatwork

OpenAI WebSearch MCP Server

OpenAI WebSearch MCP Server (TypeScript) πŸ”

TypeScript Bun MCP Compatible License: MIT

A TypeScript MCP server that provides intelligent web search capabilities using OpenAI's reasoning models and Web Search API. Built with Bun for blazing-fast performance.

What is MCP? The Model Context Protocol allows AI assistants like Claude to connect to external tools and data sources. This server adds web search capabilities to your AI assistant.

Table of Contents

✨ Features

  • πŸ” OpenAI Web Search API: Direct integration with OpenAI's Web Search API

  • 🌍 Localized Results: Support for location-based search customization

  • πŸ“ Rich Type Safety: Full TypeScript types for all parameters and responses

  • πŸš€ Bun-Powered: Lightning-fast runtime and package management

  • πŸ”§ Flexible Configuration: Environment variable support for easy deployment

  • πŸ“š Source Citations: Automatic extraction and formatting of web sources

πŸš€ Quick Start

Prerequisites

  1. Bun runtime (v1.2 or higher)

    curl -fsSL https://bun.sh/install | bash
  2. OpenAI API Key with Web Search API access

    • Get your API key from OpenAI Platform

    • Ensure your account has access to the Web Search API

Installation

# 1. Clone the repository git clone https://github.com/yourusername/openai-websearch-mcp.git cd openai-websearch-mcp # 2. Install dependencies bun install # 3. Set up environment variables cp .env.example .env # 4. Edit .env and add your OpenAI API key # OPENAI_API_KEY=sk-your-api-key-here # OPENAI_DEFAULT_MODEL=gpt-5-mini

Testing the Server

Before integrating with an MCP client, test that the server works:

# Run the server directly (it will wait for MCP protocol messages) bun run start # Or test with MCP Inspector (recommended) bunx @modelcontextprotocol/inspector bun run src/index.ts

If the server starts successfully, you'll see:

openai-websearch-mcp v1.0.0 running on stdio Default model: gpt-4o-search-preview

βš™οΈ Configuration

Environment Variables

The server requires the following environment variables:

Variable

Description

Required

Default

OPENAI_API_KEY

Your OpenAI API key

Yes

-

OPENAI_DEFAULT_MODEL

Default model to use

No

gpt-4o-search-preview

Create a .env file in the project root:

OPENAI_API_KEY=sk-your-api-key-here OPENAI_DEFAULT_MODEL=gpt-4o-search-preview

MCP Client Configuration

Configure your MCP client to connect to this server. Choose either the published package (recommended) or local development setup.

Claude Desktop

  1. Find your config file location:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

    • Windows: %APPDATA%\Claude\claude_desktop_config.json

    • Linux: ~/.config/Claude/claude_desktop_config.json

  2. Add this server configuration:

Option 1: Using npx (recommended for published package)

{ "mcpServers": { "openai-websearch-mcp": { "command": "npx", "args": ["-y", "openai-websearch-mcp"], "env": { "OPENAI_API_KEY": "sk-your-api-key-here", "OPENAI_DEFAULT_MODEL": "gpt-4o-search-preview" } } } }

Option 2: Using bunx (alternative for Bun users)

{ "mcpServers": { "openai-websearch-mcp": { "command": "bunx", "args": ["openai-websearch-mcp"], "env": { "OPENAI_API_KEY": "sk-your-api-key-here", "OPENAI_DEFAULT_MODEL": "gpt-4o-search-preview" } } } }

Option 3: Local development setup

{ "mcpServers": { "openai-websearch-mcp": { "command": "bun", "args": ["run", "/absolute/path/to/openai-websearch-mcp/src/index.ts"], "env": { "OPENAI_API_KEY": "sk-your-api-key-here", "OPENAI_DEFAULT_MODEL": "gpt-4o-search-preview" } } } }
  1. Restart Claude Desktop

  2. Look for the πŸ”Œ icon in Claude to verify the server is connected

Cursor

  1. Open Cursor Settings (Cmd/Ctrl + ,)

  2. Search for "MCP" in settings

  3. Add server configuration (same format as Claude Desktop above)

  4. Restart Cursor

Other MCP Clients

Any MCP-compatible client can use this server with the stdio transport:

Using npx:

npx -y openai-websearch-mcp

Using bunx:

bunx openai-websearch-mcp

Local development:

bun run /absolute/path/to/openai-websearch-mcp/src/index.ts

πŸ› οΈ Available Tools

Performs intelligent web search with AI reasoning capabilities.

Parameters

Parameter

Type

Required

Description

Default

input

string

Yes

The search query or question

-

model

string

No

AI model to use

gpt-4o-search-preview

user_location

object

No

Location for localized results (must include type: "approximate" with country/city/region)

null

Supported Models

All models support OpenAI's Web Search API:

  • gpt-4o-search-preview - High-quality web search with comprehensive results (default)

  • gpt-4o-mini-search-preview - Faster web search with efficient performance

  • gpt-5-search-api - Advanced search capabilities

πŸ’¬ Usage Examples

Once configured in your MCP client (Claude Desktop, Cursor, etc.), simply ask questions that require web search:

"What are the latest developments in AI?"

The AI assistant will automatically use openai_web_search with the default model.

"What tech meetups are happening in San Francisco this week?"

You can provide location context for more relevant local results.

Specific Model Selection

"Use gpt-4o-mini-search-preview to search for: Python async best practices"

Choose a specific model for your search needs (speed vs quality trade-off).

Common Use Cases

  • πŸ“° News & Current Events: "What happened in tech news today?"

  • πŸ“Š Research: "Latest papers on transformer architectures"

  • πŸ—ΊοΈ Local Information: "Best coffee shops near me"

  • πŸ’» Technical Documentation: "FastAPI async database patterns"

  • 🎯 Product Research: "Compare M3 MacBook Pro vs Air"

  • πŸ“ˆ Market Data: "Current AI startup funding trends"

πŸ€– Model Selection Guide

Standard Web Search (Default)

  • Recommended: gpt-4o-search-preview (default)

  • Use Case: General web search, current information, comprehensive results

  • Benefits: High-quality responses with source citations

  • Recommended: gpt-4o-mini-search-preview

  • Use Case: Quick queries, real-time information, faster responses

  • Benefits: Lower latency, cost-effective for frequent searches

  • Recommended: gpt-5-search-api

  • Use Case: Complex search queries, advanced capabilities

  • Benefits: Latest search features and capabilities

πŸ“¦ Development

# Install dependencies bun install # Run in development mode with auto-reload bun run dev # Build for production bun run build # Run tests bun test # Type checking bun run typecheck # Lint code bun run lint

πŸ“€ Publishing to NPM

Prerequisites

  1. NPM Account: Create one at npmjs.com/signup if you don't have one

  2. Email Verified: Ensure your NPM account email is verified

Before Publishing

  1. Update package.json metadata:

    • Replace YOUR_USERNAME in repository.url with your GitHub username

    • Replace YOUR_USERNAME in homepage with your GitHub username

    • Replace YOUR_USERNAME in bugs.url with your GitHub username

    • Optionally add author field: "author": "Your Name <your.email@example.com>"

  2. Remove any test dependencies:

    • Check for any file: references in dependencies

    • Remove test tarballs from the project directory

Publishing Steps

# 1. Login to NPM (one-time setup) npm login # Enter your username, password, and email when prompted # 2. Verify you're logged in npm whoami # 3. Check what will be published (dry run) npm publish --dry-run # 4. Publish to NPM! npm publish

What Happens During Publish

The prepublishOnly script automatically runs:

  1. bun run typecheck - Verifies TypeScript types

  2. bun run build - Builds the dist/ folder

  3. NPM packages and uploads only files in the files array (dist/, README.md, LICENSE)

After Publishing

  • Your package will be available at: https://www.npmjs.com/package/openai-websearch-mcp

  • Users can install it with: npx openai-websearch-mcp or bunx openai-websearch-mcp

  • It will appear in NPM search results

Publishing Updates

When you need to publish a new version:

# Update version (choose one) npm version patch # Bug fixes: 1.0.0 -> 1.0.1 npm version minor # New features: 1.0.0 -> 1.1.0 npm version major # Breaking changes: 1.0.0 -> 2.0.0 # Publish the new version npm publish

Optional: Scoped Package

To publish under your username (e.g., @yourusername/openai-websearch-mcp):

  1. Change "name" in package.json to "@yourusername/openai-websearch-mcp"

  2. Publish with: npm publish --access public

Verify Publication

After publishing, verify your package:

# Check package info npm info openai-websearch-mcp # Test installation npx openai-websearch-mcp@latest

πŸ—οΈ Project Structure

openai-websearch-mcp/ β”œβ”€β”€ src/ β”‚ β”œβ”€β”€ index.ts # MCP server entry point β”‚ β”œβ”€β”€ types/ β”‚ β”‚ β”œβ”€β”€ openai.ts # OpenAI API types β”‚ β”‚ β”œβ”€β”€ mcp.ts # MCP tool types β”‚ β”‚ └── config.ts # Configuration types β”‚ β”œβ”€β”€ tools/ β”‚ β”‚ └── webSearch.ts # Web search tool implementation β”‚ β”œβ”€β”€ utils/ β”‚ β”‚ β”œβ”€β”€ config.ts # Environment config handler β”‚ β”‚ β”œβ”€β”€ models.ts # Model validation & defaults β”‚ β”‚ └── errors.ts # Error handling utilities β”‚ └── constants.ts # Model lists, defaults β”œβ”€β”€ package.json β”œβ”€β”€ tsconfig.json └── README.md

πŸ› Debugging & Troubleshooting

Using MCP Inspector

The MCP Inspector provides a web UI for testing your server:

bunx @modelcontextprotocol/inspector bun run src/index.ts

This will open a browser interface where you can:

  • See available tools

  • Test tool calls with different parameters

  • View request/response logs

  • Debug errors

Common Issues

"OPENAI_API_KEY environment variable is required"

Solution: Create a .env file with your API key:

echo "OPENAI_API_KEY=sk-your-key-here" > .env

"Invalid OpenAI API key format"

Solution: Ensure your API key starts with sk-

"Server not appearing in Claude Desktop"

Solutions:

  1. Verify the absolute path in your config is correct

  2. Restart Claude Desktop completely

  3. Check Claude's logs:

    • macOS: ~/Library/Logs/Claude/

    • Windows: %APPDATA%\Claude\logs\

    • Linux: ~/.config/Claude/logs/

"Command 'bun' not found"

Solution: Install Bun:

curl -fsSL https://bun.sh/install | bash

Logging

The server logs to stderr. To see detailed logs:

# Run with output visible bun run src/index.ts 2>&1 | tee server.log

Testing Individual Components

# Type checking bun run typecheck # Run specific tests (if implemented) bun test # Check if OpenAI API key works # (Creates a simple test script to verify) echo 'import OpenAI from "openai"; const client = new OpenAI(); console.log("API key valid");' | bun run -

πŸ“„ License

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

πŸ™ Acknowledgments

-
security - not tested
F
license - not found
-
quality - not tested

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/luchiniatwork/openai-websearch-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server