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📌 What Really Happens When You Ask a Cursor a Question with GitHub MCP Integrated 📌
- When you ask a prompt like 'Show my open PRs' in Cursor, integrated with GitHub MCP, a complex pipeline of AI reasoning is triggered.
- The process involves Cursor's AI models interpreting the request, selecting appropriate tools, and utilizing GitHub APIs through the Model Context Protocol (MCP).
- The request starts in the Cursor chat interface, which bundles the prompt, chat history, code snippets, and metadata into a payload sent to a cloud model.
- Cursor determines the need for a tool, like the list_pull_requests tool from the GitHub MCP server, and collects necessary parameters like repository details and user credentials.
- A JSON-RPC request is formatted by Cursor and sent to the GitHub MCP server, which securely interacts with GitHub's API to retrieve pull request data.
- The MCP server authenticates with GitHub, fetches open pull requests, and returns structured JSON responses back to Cursor.
- Cursor incorporates the tool's response into the prompt for the Language Model (LLM) to convert into a readable format, showing the user their open PRs.
- The development cycle continues as Cursor processes user interactions, enabling context-aware intelligence and seamless workflow integration.
- This intricate workflow showcases secure access to real services, structured memory use, and tool-enhanced interactions, defining a new paradigm for developer workflows.
- Cursor, combined with MCP, creates an AI-driven workflow that enhances developer experiences by providing contextual reasoning and seamless tool integration.
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