Vectorify Php

Vectorify package for PHP

[](https://packagist.org/packages/vectorifyai/vectorify-php) [](https://packagist.org/packages/vectorifyai/vectorify-php) [](https://github.com/vectorifyai/vectorify-php/actions/workflows/tests.yml) [](LICENSE.md)

Vectorify is the end-to-end AI connector for PHP, letting you query and explore your data in natural language in seconds.

To interact with your data, you have four primary methods to choose from:

1. Use the Chats page within our platform (fastest)
2. Embed the Chatbot into your PHP app (turn data querying into a product feature)
3. Add the MCP server to ChatGPT, Claude, etc. (use your data anywhere you work)
4. Call the REST API endpoints (build custom integrations and workflows)

Unlike text-to-SQL tools that expose your entire database and take 30+ seconds per query, Vectorify uses proven RAG technology to deliver accurate answers in ['type' => 'string'], 'status' => [ 'type' => 'enum', 'options' => ['draft', 'sent', 'paid'], ] ], );

// Create items $items = [ new ItemObject( id: '123', data: [ 'customername' => 'John Doe', 'status' => 'draft', 'amount' => '100', 'currency' => 'USD', 'duedate' => '2023-10-01' ], metadata: [ 'customer_name' => 'John Doe', 'status' => 'draft' ], tenant: 987, url: 'https://example.com/invoice/123', ), ];

// Upsert data $upsertObject = new UpsertObject($collection, $items); $success = $vectorify->upserts->create($upsertObject);

if ($success) { echo "Data upserted successfully!\n"; }

// Query data $queryObject = new QueryObject( text: 'how many invoices are in draft status?', collections: ['invoices'], tenant: 987, identifier: [ 'id' => '123', 'name' => 'John Doe', 'email' => 'john@example.com', ] );

$result = $vectorify->query->send($queryObject);

if ($result !== false) { print_r($result); }

## Features

- **Rate Limiting**: Automatic rate limit handling with exponential backoff
- **Retry Logic**: Built-in retry mechanism for failed requests
- **Type Safety**: Fully typed objects for better development experience
- **Error Handling**: Comprehensive error handling and logging
- **PSR-7 Compatible**: Uses PSR-7 HTTP message interfaces

## API Methods

### Upsert

Create or update items in your Vectorify collection:

```php
$upsertObject = new UpsertObject($collection, $items);
$success = $vectorify->upserts->create($upsertObject);

Query

Ask questions about your data:

$queryObject = new QueryObject('your question here');
$result = $vectorify->query->send($queryObject);

Configuration

Timeout

You can configure the request timeout when initializing the client:

$vectorify = new Vectorify('your-api-key', 60); // 60 seconds timeout

Debug Logging

Enable debug logging by defining a constant:

define('VECTORIFY_DEBUG', true);

Error Handling

The SDK includes comprehensive error handling:

• Rate Limiting: Automatically handles 429 responses with appropriate delays
• Server Errors: Retries server errors (5xx) with exponential backoff
• Client Errors: Returns null or false for client errors (4xx)
• Network Errors: Retries network-related errors

Changelog

Please see [Releases](../../releases) for more information on what has changed recently.

Contributing

Pull requests are more than welcome. You must follow the PSR coding standards.

Security

Please review our security policy on how to report security vulnerabilities.

License

The MIT License (MIT). Please see [LICENSE](LICENSE.md) for more information.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: vectorifyai
• Source: vectorifyai/vectorify-php
• License: MIT
• Homepage: https://vectorify.ai

Install and usage instructions live in the source repository linked above.