# Integrations

Connect your existing content from various platforms and transform them into searchable knowledge that works with AI applications.

## Available Integrations

**Desktop and Local Files**

* [**Rememberizer App**](/personal-use/integrations/rememberizer-app.md) - Desktop application for processing local files with support for documents, presentations, code files, and more

**Cloud Storage**

* [**Google Drive Integration**](/personal-use/integrations/rememberizer-google-drive-integration.md) - Connect documents and files from your Google Drive
* [**Dropbox Integration**](/personal-use/integrations/rememberizer-dropbox-integration.md) - Access and search files in your Dropbox account

**Communication Platforms**

* [**Slack Integration**](/personal-use/integrations/rememberizer-slack-integration.md) - Import messages, files, and conversations from Slack workspaces
* [**Gmail Integration**](/personal-use/integrations/rememberizer-gmail-integration.md) - Search through emails, attachments, and conversations

**AI and Memory**

* [**Memory Integration**](/personal-use/integrations/rememberizer-memory-integration.md) - Save and retrieve AI conversation history
* [**MCP Servers**](/personal-use/integrations/rememberizer-mcp-servers.md) - Connect with MCP servers

**Management**

* [**Manage Third-Party Apps**](/personal-use/integrations/manage-third-party-apps.md) - Control which external applications can access your knowledge

## How It Works

1. Connect your data sources using secure OAuth authentication
2. Rememberizer processes content and creates vector embeddings
3. Organize knowledge using [Mementos](/personal-use/personal/mementos-filter-access.md) for access control
4. [Search across all sources](/personal-use/personal/search-your-knowledge.md) with semantic search


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.rememberizer.ai/personal-use/integrations.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.