> ## 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.

# Dify

> Integrate MemMachine memory tools into your Dify workflows

For the full plugin source code and contribution guidelines, see the official **[Dify Integration](https://github.com/MemMachine/MemMachine/tree/main/integrations/dify)** in the repository.

## Overview

The MemMachine Dify plugin allows you to seamlessly integrate persistent memory into your Dify applications. By adding MemMachine as a tool provider, your Dify agents can store chronological interactions (Episodic) and retrieve distilled knowledge (Semantic), enabling a deeper level of context awareness across user sessions.

## Configuration

When adding the MemMachine plugin to Dify, you will need to configure the following credentials:

| Variable              | Description                                | Default                        |
| --------------------- | ------------------------------------------ | ------------------------------ |
| `memmachine_api_key`  | Your MemMachine API Key for authentication | (Required)                     |
| `memmachine_base_url` | The URL of your MemMachine backend service | `https://api.memmachine.ai/v2` |

<Info>
  The `memmachine_base_url` is optional. If left empty, the plugin will default to the MemMachine Cloud API. If you are self-hosting, ensure you provide your local server address (e.g., `http://localhost:8080`).
</Info>

## Setup Guide

<Steps>
  <Step title="Build and Package">
    Navigate to the integration directory and run the build script to generate the `.plugin` file:

    ```bash theme={null}
    cd integrations/dify
    # Build the plugin package
    python build_plugin.py --enable-base-url-credential
    ```
  </Step>

  <Step title="Install in Dify">
    A. Open your Dify dashboard.
    B. Navigate to the **Plugins** tab.
    C. Upload the generated `.plugin` file.
  </Step>

  <Step title="Configure Credentials">
    Navigate to **Tools > MemMachine** in Dify and enter your configuration:

    A. Paste your **API Key**.
    B. (Optional) Enter your **Base URL** if you are not using the cloud service.
    C. Click **Save**.
  </Step>
</Steps>

## Usage

Once installed, you can add MemMachine tools to any Dify **Chatflow** or **Agent**.

### Memory Search

Use the `search_memory` tool to retrieve relevant context. In a Chatflow, you can map the query input using Jinja2 templates:

Code snippet

```
{{ sys.query }}
```

### Memory Storage

Use the `add_memory` tool within your nodes to persist important information from the conversation, ensuring the agent "remembers" it in future sessions.

***

## Developer Guide (Contributors)

If you wish to modify the plugin behavior or develop new tools for the Dify provider:

### Requirements

* Python 3.12+
* Dify Plugin CLI (`dify`)
* `jinja2` (for build-time template rendering)

### Development Workflow

The source of truth for the plugin provider and tool definitions is located in the `templates/` directory.

1. **Modify Templates:** Edit files in `templates/` or add new tools to `tools/`.

2. **Rebuild:** Run `python build_plugin.py` to render the `provider/` files.

3. **Manual Package:**

   Bash

   ```
   dify-plugin plugin package ./integrations/dify
   ```

### Repo Hygiene

Note that generated provider files are ignored by git. Always modify the files in `templates/` and use the build script to ensure your changes are correctly propagated to the packaged plugin.

## Requirements

* A Dify instance (Cloud or Self-hosted)
* MemMachine server running (default: [http://localhost:8080](http://localhost:8080)) or Cloud account
* Python 3.12+ (for building/contributing)