import * as vscode from 'vscode';
import * as path from 'path';
import { spawn, ChildProcess } from 'child_process';
let mcpServerProcess: ChildProcess | null = null;
export function activate(context: vscode.ExtensionContext) {
console.log('Natural Voice MCP extension activated');
// Register start server command
const startServerCmd = vscode.commands.registerCommand(
'natural-voice-mcp.startServer',
() => startMcpServer(context)
);
// Register detect AI patterns command
const detectPatternsCmd = vscode.commands.registerCommand(
'natural-voice-mcp.detectAIPatterns',
() => detectAIPatternsInSelection()
);
context.subscriptions.push(startServerCmd, detectPatternsCmd);
// Auto-start if configured
const config = vscode.workspace.getConfiguration('natural-voice-mcp');
if (config.get('autoStart')) {
startMcpServer(context);
}
// Register MCP server info for Antigravity/Claude
registerMcpServer(context);
}
function startMcpServer(context: vscode.ExtensionContext) {
if (mcpServerProcess) {
vscode.window.showInformationMessage('Natural Voice MCP server is already running');
return;
}
const serverPath = path.join(context.extensionPath, 'mcp-server', 'index.js');
mcpServerProcess = spawn('node', [serverPath], {
stdio: ['pipe', 'pipe', 'pipe']
});
mcpServerProcess.on('error', (err) => {
vscode.window.showErrorMessage(`Failed to start MCP server: ${err.message}`);
mcpServerProcess = null;
});
mcpServerProcess.on('exit', (code) => {
if (code !== 0) {
vscode.window.showWarningMessage(`MCP server exited with code ${code}`);
}
mcpServerProcess = null;
});
vscode.window.showInformationMessage('Natural Voice MCP server started');
}
async function detectAIPatternsInSelection() {
const editor = vscode.window.activeTextEditor;
if (!editor) {
vscode.window.showWarningMessage('No active editor');
return;
}
const selection = editor.selection;
const text = editor.document.getText(selection);
if (!text) {
vscode.window.showWarningMessage('No text selected');
return;
}
// Run the detection logic
const patterns = detectAIPatterns(text);
// Show results in output channel
const outputChannel = vscode.window.createOutputChannel('Natural Voice');
outputChannel.clear();
outputChannel.appendLine('=== AI Pattern Detection Results ===\n');
outputChannel.appendLine(`Score: ${patterns.score}/100`);
outputChannel.appendLine(`Verdict: ${patterns.verdict}\n`);
if (patterns.ai_tells.length > 0) {
outputChannel.appendLine('AI Tells Found:');
patterns.ai_tells.forEach((tell: string) => outputChannel.appendLine(` • ${tell}`));
outputChannel.appendLine('');
}
if (patterns.issues.length > 0) {
outputChannel.appendLine('Issues:');
patterns.issues.forEach((issue: string) => outputChannel.appendLine(` • ${issue}`));
}
outputChannel.show();
}
function detectAIPatterns(text: string): { ai_tells: string[], issues: string[], score: number, verdict: string } {
const patterns = {
ai_tells: [] as string[],
score: 100,
issues: [] as string[],
verdict: ''
};
// Corporate enthusiasm
const enthusiasmPhrases = [
"thrilled to announce",
"excited to share",
"delighted to present",
"over the moon",
"humbled and honored",
];
enthusiasmPhrases.forEach((phrase) => {
if (text.toLowerCase().includes(phrase)) {
patterns.ai_tells.push(`Corporate enthusiasm: "${phrase}"`);
patterns.score -= 10;
}
});
// Formal transitions
const formalTransitions = [
"furthermore",
"moreover",
"additionally",
"in conclusion",
"it is worth noting",
];
formalTransitions.forEach((phrase) => {
if (text.toLowerCase().includes(phrase)) {
patterns.ai_tells.push(`Formal transition: "${phrase}"`);
patterns.score -= 5;
}
});
// Check for contractions
const hasContractions = /\b(don't|can't|won't|isn't|aren't|wasn't|weren't|haven't|hasn't|hadn't|wouldn't|shouldn't|couldn't)\b/i.test(text);
if (!hasContractions && text.length > 100) {
patterns.issues.push("No contractions found (sounds stiff)");
patterns.score -= 10;
}
// Em dash overuse
const emDashCount = (text.match(/—/g) || []).length;
const wordCount = text.split(/\s+/).length;
if (emDashCount > 2 && wordCount < 500) {
patterns.issues.push(`Em dash overuse (${emDashCount} in ${wordCount} words)`);
patterns.score -= 10;
}
patterns.score = Math.max(0, patterns.score);
if (patterns.score > 80) {
patterns.verdict = "Sounds human ✓";
} else if (patterns.score > 50) {
patterns.verdict = "Some AI tells present";
} else {
patterns.verdict = "Strong AI indicators";
}
return patterns;
}
function registerMcpServer(context: vscode.ExtensionContext) {
const serverPath = path.join(context.extensionPath, 'mcp-server', 'index.js');
const provider = vscode.lm.registerMcpServerDefinitionProvider(
'natural-voice-mcp.servers',
{
provideMcpServerDefinitions: () => {
return [
new vscode.McpStdioServerDefinition(
'Natural Voice MCP',
process.execPath,
[serverPath]
)
];
}
}
);
context.subscriptions.push(provider);
}
export function deactivate() {
if (mcpServerProcess) {
mcpServerProcess.kill();
mcpServerProcess = null;
}
}
