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mcp-aoai-web-browsingA minimal Model Context Protocol 🖥️ server/client🧑‍💻with Azure OpenAI and 🌐 web browser control via Playwright.

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Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

mcp-aoai-web-browsing is a minimal server/client application implementation utilizing the Model Context Protocol (MCP) and Azure OpenAI. The MCP server is built with FastMCP and utilizes Playwright for web browser control. The application enables secure, controlled interactions between AI applications and local or remote resources. The MCP response about tools will be converted to the OpenAI function calling format, and a bridge converts the MCP server response to the OpenAI function calling format. This customization is based on the MCP-LLM Bridge implementation. The client_bridge supports both in-process and external (stdio) MCP server connections, allowing it to be reused by different clients, such as Claude Code, VS Code, and custom scripts. The application also supports using external clients, such as Claude Desktop, through the mcp.json configuration. Additionally, the client_bridge can connect to external MCP servers via stdio from Python. This application utilizes Azure OpenAI for deployment, and configuration requires filling in values in the .env file for Azure OpenAI endpoints, API keys, and other necessary information. The application supports various configuration options, including using different libraries for dependency management and renaming configuration files. Overall, mcp-aoai-web-browsing is a tool for utilizing the Model Context Protocol and Azure OpenAI for web browsing and other purposes.

Key features

  • MCP server with FastMCP
  • Azure OpenAI integration
  • Web browser control via Playwright
  • Client_bridge for in-process and external (stdio) MCP server connections
  • Conversion of MCP responses to OpenAI function calling format

Pricing

Model
Free
Category
MCP Servers
Rating
No reviews yet

Use cases

Automated Web Browsing

Use the MCP server and client to automate web browsing tasks, such as data scraping or web page navigation, with the help of Azure OpenAI and Playwright.

AI-Powered Browser Interactions

Integrate the MCP server and client with AI applications, such as Claude Code or VS Code, to enable AI-powered browser interactions and automation.

Pros & Cons

Pros

  • Enables secure and controlled interactions between AI applications and local or remote resources
  • Supports Azure OpenAI and OpenAI-compatible LLMs
  • Allows for web browser control and automation via Playwright
  • Reusable client_bridge for multiple clients and applications

Cons

  • Requires configuration and setup of Azure OpenAI endpoint, API key, and deployment model
  • Limited support for dependency management libraries other than 'uv'
  • May require additional setup for external clients and integrations

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Q&A

What is the learning curve?

The tool requires configuration and setup of Azure OpenAI endpoint, API key, and deployment model, which may require technical expertise and additional setup for external clients and integrations.

Asked by Bianca Ferreira · Dec 6, 2025

What is the use case for this tool?

The tool enables secure and controlled interactions between AI applications and local or remote resources, with potential use cases including web browser automation and AI-driven workflows.

Asked by Kwame Mensah · Nov 19, 2025

What integrations are supported?

The tool supports Azure OpenAI integration, and web browser control via Playwright, with reusable client_bridge for multiple clients and applications like Claude Code and VS Code.

Asked by Marcus Bell · Oct 29, 2025

What is the pricing model?

Pricing details are not provided, please contact the developer for more information.

Asked by Constantin Ionescu · Sep 21, 2025

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