> ## Documentation Index
> Fetch the complete documentation index at: https://docs.memmachine.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# MemMachineProject

> Class for managing the lifecycle, configuration, and memory scaling of a specific project.

## Overview

The `MemMachineProject` class provides methods to manage and interact with projects within the MemMachine ecosystem\[cite: 1]. It serves as a middle-tier controller, allowing you to create projects, check memory usage, and spawn dedicated memory management instances.

### Key Features

* **Project Lifecycle:** Create, retrieve, and delete project entities on the server.
* **Memory Factory:** Initialize `MemMachineMemory` instances scoped to this project.
* **Usage Metrics:** Retrieve the total count of episodic memories stored within the project.

***

## Constructor

### `new MemMachineProject()`

Initializes a project instance. This is typically accessed via `client.project()`.

```typescript theme={null}
new MemMachineProject(client: AxiosInstance, projectContext: ProjectContext)
```

| **Parameter**    | **Type**                                         | **Description**                                     |
| ---------------- | ------------------------------------------------ | --------------------------------------------------- |
| `client`         | `AxiosInstance`                                  | Internal Axios instance for API communication.      |
| `projectContext` | [`ProjectContext`](../interfaces/ProjectContext) | Scoping identifiers like `org_id` and `project_id`. |

***

## Properties

| **Property**     | **Type**                                         | **Description**                              |
| ---------------- | ------------------------------------------------ | -------------------------------------------- |
| `client`         | `AxiosInstance`                                  | The underlying HTTP client.                  |
| `projectContext` | [`ProjectContext`](../interfaces/ProjectContext) | The active organizational and project scope. |

***

## Methods

### `create()`

Initializes the project on the MemMachine server.

```typescript theme={null}
create(options?: CreateProjectOptions): Promise<Project>
```

* **Parameters:** `options` — [`CreateProjectOptions`](../interfaces/CreateProjectOptions) (Optional).
* **Throws:** [`MemMachineAPIError`](./MemMachineAPIError) if the request fails.

### `get()`

Retrieves the current metadata and state of the project from the server.

```typescript theme={null}
get(): Promise<Project>
```

* **Returns:** `Promise<Project>` — The current project data model.

### `getEpisodicCount()`

Retrieves the total number of episodic memories associated with this project.

```typescript theme={null}
getEpisodicCount(): Promise<number>
```

### `memory()`

Creates a `MemMachineMemory` instance scoped to this project.

```typescript theme={null}
memory(memoryContext?: MemoryContext): MemMachineMemory
```

* **Parameters:** `memoryContext` — [`MemoryContext`](../interfaces/MemoryContext) (Optional).

### `delete()`

Permanently removes the project and all associated memories from the server.

```typescript theme={null}
delete(): Promise<null>
```

***

## Usage Example

```typescript theme={null}
const project = client.project({ org_id: 'org_123', project_id: 'proj_456' });

// 1. Create the project if it doesn't exist
await project.create({ description: 'AI Assistant Context' });

// 2. Check the memory footprint
const count = await project.getEpisodicCount();
console.log(`Current memory count: ${count}`);

// 3. Access memory operations
const memory = project.memory();
```

<Note> This class is the recommended gateway for memory management. Always use `project.memory()` to ensure your operations are correctly scoped to your organization and project ID. </Note>