---
title: Mastra
---

# Mastra

[Mastra](https://mastra.ai/) is a Typescript framework to build AI applications and features quickly. It gives you the set of primitives you need: workflows, agents, RAG, integrations, syncs and evals. You can run Mastra on your local machine, or deploy to a serverless cloud.

Qdrant is available as a vector store in Mastra node to augment application with retrieval capabilities.

## Setup

```bash
npm install @mastra/core
```

## Usage

```typescript
import { QdrantVector } from "@mastra/rag";

const qdrant = new QdrantVector({
  url: "https://xyz-example.eu-central.aws.cloud.qdrant.io:6333"
  apiKey: "<YOUR_API_KEY>",
  https: true
});
```

## Constructor Options

| Name   | Type      | Description                                                                                           |
|--------|-----------|-------------------------------------------------------------------------------------------------------|
| `url`  | `string`  | REST URL of the Qdrant instance. Eg. <https://xyz-example.eu-central.aws.cloud.qdrant.io:6333>         |
| `apiKey` | `string` | Optional Qdrant API key                                                                              |
| `https` | `boolean` | Whether to use TLS when setting up the connection. Recommended.                                     |

## Methods

### `createIndex()`

| Name       | Type                                     | Description                                     | Default Value |
|------------|------------------------------------------|-------------------------------------------------|--------------|
| `indexName` | `string`                                | Name of the index to create                     |              |
| `dimension` | `number`                                | Vector dimension size                           |              |
| `metric`    | `string`                                | Distance metric for similarity search           | `cosine`     |

### `upsert()`

| Name        | Type                      | Description                             | Default Value |
|-------------|---------------------------|-----------------------------------------|--------------|
| `vectors`   | `number[][]`              | Array of embedding vectors              |              |
| `metadata`  | `Record<string, any>[]`   | Metadata for each vector (optional)     |              |
| `namespace` | `string`                  | Optional namespace for organization     |              |

### `query()`

| Name       | Type                    | Description                                 | Default Value |
|------------|-------------------------|---------------------------------------------|--------------|
| `vector`   | `number[]`              | Query vector to find similar vectors       |              |
| `topK`     | `number`                | Number of results to return (optional)     | `10`         |
| `filter`   | `Record<string, any>`   | Metadata filters for the query (optional)  |              |

### `listIndexes()`

Returns an array of index names as strings.

### `describeIndex()`

| Name        | Type     | Description                      |
|-------------|----------|----------------------------------|
| `indexName` | `string` | Name of the index to describe    |

#### Returns

```typescript
interface IndexStats {
  dimension: number;
  count: number;
  metric: "cosine" | "euclidean" | "dotproduct";
}
```

### `deleteIndex()`

| Name        | Type     | Description                      |
|-------------|----------|----------------------------------|
| `indexName` | `string` | Name of the index to delete      |

## Response Types

Query results are returned in this format:

```typescript
interface QueryResult {
  id: string;
  score: number;
  metadata: Record<string, any>;
}
```

## Further Reading

- [Mastra Examples](https://github.com/mastra-ai/mastra/tree/main/examples)
- [Mastra Documentation](http://mastra.ai/docs/)