Code MCP Server

# VS Code MCP Project Hints ## Project Structure The VS Code MCP (Model Context Protocol) project consists of two main components: - `/server`: MCP server implementation that handles protocol communication - `/extension`: VS Code extension that provides native VS Code integration ## Key Concepts - MCP (Model Context Protocol): A protocol for AI agents to interact with external tools and services - The server acts as a bridge between AI agents (like Goose) and VS Code - The extension provides native VS Code features like diff viewing and file manipulation ## Common Operations - File changes are staged through the server and reviewed via VS Code diff viewer - The extension runs on a dynamic port, stored in `ag-VS Code-mcp-extension.port` - Communication between server and extension happens over TCP socket ## Available Tools - `create_diff`: Shows file changes in VS Code diff viewer for approval - Required params: filePath, newContent - Optional params: description - `check_extension_status`: Verifies VS Code extension is installed and responding - `get_extension_port`: Gets the current port number for extension communication ## File Locations - Extension port file: `os.tmpdir()/ag-vscode-mcp-extension-registry.json` or `/tmp/ag-vscode-mcp-extension-registry.json` - Server log file: `server/vscode-mcp-server-debug.log` ## Best Practices - Always use absolute paths when working with files - Handle cleanup of temporary files in both success and error cases - Provide descriptive titles for diffs to help users understand changes - Check extension connectivity before attempting operations that require it ## Common Issues - Extension port file may not exist if extension isn't running - File paths need to be resolved to absolute paths - Temporary files should be cleaned up after diff operations ## Environment Variables - `PROJECTS_BASE_DIR`: Base directory for VS Code projects ## How to solve problems in this codebase If we are having challenges easily solving a problem, take a moment to reflect on 5 or 6 possible sources of the problem. Then distill those into 1 or 2 of the mostly likely options. Add logs to help prove or disprove these possibilities before you move on to attempting to fix the problem with code.