Basic chatbots get much of the publicity associated with modern AI platforms, but they have limited use cases, providing a simple natural language interface to search tools. It's certainly useful, provided you implement fine-tuning and grounding in your own data, but it is still best thought of as an extension of existing search tools. AI has other uses: embedding the technology inside enterprise IT stacks, providing advanced filtering and summarization, using it for translation and voice recognition, and simplifying interactions through natural language.
MCP gives all three context. MCP stands for Model Context Protocol and was developed and open-sourced by Anthropic to standardize integrations between AI and the tools and data sources that can provide critical information in ways that enable LLMs to understand and take action. Instead of every service building out an integration for every AI agent, MCP defines a protocol where any application can maintain a single MCP server implementation that exposes its functionality,
Product manager Allie Barrie said that Visual Studio can now connect to local or remote MCP servers, configured using a file called .mcp.json which can be in a user profile, for global use, or in an individual solution. Developers can add MCP servers either by editing this file directly, or using settings in the GitHub Copilot chat window. There is also provision for one-click installation from the web. OAuth authentication is supported, for example to allow the MCP tools to have GitHub access.