> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentfront.dev/llms.txt
> Use this file to discover all available pages before exploring further.
# Integrations Overview
> Integrate VectoriaDB with popular frameworks and tools
VectoriaDB integrates seamlessly with popular frameworks and tools.
## Available Integrations
Intelligent tool discovery for MCP servers
Semantic search in sandboxed environments
REST API integration with Express.js
Full-stack search with Next.js
## Integration Pattern
All integrations follow a similar pattern:
```ts title="src/integration-pattern.ts" theme={"theme":{"light":"snazzy-light","dark":"dark-plus"}}
import { VectoriaDB, DocumentMetadata } from 'vectoriadb';
// 1. Define your metadata interface
interface MyDocument extends DocumentMetadata {
title: string;
category: string;
}
// 2. Create a singleton instance
let db: VectoriaDB | null = null;
export async function getDB() {
if (db) return db;
db = new VectoriaDB({
// Configuration...
});
await db.initialize();
return db;
}
// 3. Use in your application
export async function search(query: string) {
const database = await getDB();
return database.search(query);
}
```
## Middleware Pattern
Create reusable middleware for VectoriaDB:
```ts title="src/middleware/vectoriadb.ts" theme={"theme":{"light":"snazzy-light","dark":"dark-plus"}}
import { Request, Response, NextFunction } from 'express';
import { VectoriaDB } from 'vectoriadb';
declare global {
namespace Express {
interface Request {
vectoriadb?: VectoriaDB;
}
}
}
export function vectoriadbMiddleware(db: VectoriaDB) {
return (req: Request, res: Response, next: NextFunction) => {
req.vectoriadb = db;
next();
};
}
// Usage
app.use(vectoriadbMiddleware(productIndex));
app.get('/search', async (req, res) => {
const results = await req.vectoriadb!.search(req.query.q as string);
res.json(results);
});
```
## Related
Complete tool discovery guide
Production deployment