Introducing Agent Mode: Seamless AI Development with Readme Integration and MCP

Join me as we dive into the world of AI-powered coding with Co-Pilot, exploring its capabilities in music, agent mode, and Model Context Protocol (MCP) integration - revolutionizing the way we develop software!

  • 1. The focus of recent music has been on co-pilot, which brings AI development capabilities to users.
  • 2. Co-pilot started with code completion, providing suggestions and full function completions as the user types.
  • 3. Chat functionality was added, allowing for more complex prompts and changes to multiple files at once.
  • 4. Agent mode is a new feature that allows for deep interaction with an agent while building tasks.
  • 5. Users can interact with the agent in real-time and set permissions for terminal interactions.
  • 6. The agent can build a complete greenfield app, perform deep refactoring across large codebases, and handle moderately complex tasks.
  • 7. An example of using agent mode is given, where a readme file with detailed instructions is used to create a basic working app in real-time.
  • 8. MCP (Model Context Protocol) is an open protocol that allows LLMs (Language Learning Models) to communicate with external data sources and references.
  • 9. MCP can be used with various technologies, such as Postgres for database access and SSE (Server-Sent Events) for running in a protected environment on a remote server.
  • 10. To use MCP in VS Code:
  • * Identify the problem and required technologies
  • * Search for an appropriate MCP server on GitHub
  • * Install and configure the MCP server with specific information (e.g., Postgres connection string)
  • * Start the local MCP server
  • 11. The user can interact with the local MCP servers through a list of available servers in VS Code.
  • 12. Copilot can be directed to use specific MCPs for tasks by being more explicit in prompts.
  • 13. In the example given, a Postgres MCP is used to pull data from a database and create a mock JSON file for testing purposes.
  • 14. The handshaking process between Copilot and the MCP involves identifying what needs to be done step by step (e.g., getting the database schema, selecting specific tables, pulling data).
  • 15. VS Code workflow is improved using GitHub's MCP server for automating tasks like committing changes to a new branch and creating PRs (Pull Requests).
  • 16. Copilot instructions can be used to pre-inject commonly used practices into every prompt, such as running security checks or adding change log entries.
  • 17. A question is answered about Gupil agent coding agent, which is seen as more of an enterprise solution due to its autonomous nature and ability for team interaction.
  • 18. Assign Issue to Copilot is mentioned, a feature that allows users to create issues in GitHub with copilot as the assignee, enabling background processing and output through PRs (Pull Requests).
  • 19. MCP can be configured under repo settings for any user who wants to use it with Assign Issue to Copilot.

Source: AI Engineer via YouTube

❓ What do you think? What are your thoughts on the ideas shared in this video? Feel free to share your thoughts in the comments!