Nextcloud MCP Server: Seamless Integration Between AI and Data Management

Overview: What is the Nextcloud MCP Server?

The Nextcloud MCP Server is a specialized platform that enables Large Language Models (LLMs) like OpenAI's GPT, Google's Gemini, or Anthropic's Claude to interact with your Nextcloud instance. This server acts as a bridge between AI applications and your data management tools, leveraging the Model Context Protocol (MCP) for seamless integration. By connecting to the Notes API within Nextcloud, it provides advanced functionalities such as creating, updating, and deleting notes, making these operations accessible through APIs designed for AI applications.

🔧 Core Features & MCP Capabilities

The Nextcloud MCP Server offers a range of powerful tools and resources that are vital for integrating Artificial Intelligence (AI) into your workflow. Here’s an overview of the key features:

Available Tools

• nc_notes_create_note: Enables LLMs to create new notes within Nextcloud.
• nc_notes_update_note: Permits updates to existing notes based on their ID.
• nc_notes_delete_note: Facilitates the deletion of specific notes through their IDs.

Available Resources

• notes://{note_id}: Provides direct access to a specific note by its unique identifier, allowing for precise data manipulation.
• notes://all: Offers access to all notes within Nextcloud, enhancing bulk operations and management.
• notes://settings: Allows access to note settings, giving control over how notes are stored and managed.
• nc://capabilities: Provides insights into the capabilities of your Nextcloud server, helping AI applications understand what they can do.

These features ensure that the Nextcloud MCP Server is a versatile tool for managing and automating tasks within Nextcloud instances using AI-driven workflows.

⚙️ MCP Architecture & Protocol Implementation

The Nextcloud MCP Server is built on top of modern web technologies and follows the Model Context Protocol (MCP) to create a seamless connection between AI applications and your data management tools. The protocol ensures that interactions are secure, efficient, and contextually rich, making it easier for LLMs to perform tasks.

Mercury Server Flow Diagram

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Mercury Data Architecture Diagram

graph TD
    D[Data Storage] --> E[API Gateway]
    E --> F[MCP Server]
    F --> G[Application Layer]
    H[User Interface] <--> G
    style D fill:#d1ffe0
    style E fill:#f5efe8
    style F fill:#e8efe8
    style G fill:#fffce2

These diagrams illustrate the flow of data and commands between an AI application (via the MCP client), the Nextcloud MCP Server, and various Nextcloud APIs. The architecture emphasizes a clear separation of concerns and efficient use of resources.

🚀 Getting Started with Installation

To install and run the Nextcloud MCP Server locally or using Docker, follow these steps:

Prerequisites

• Python 3.8+
• Access to a Nextcloud instance

Local Installation

1. Clone the repository:

   git clone https://github.com/cbcoutinho/nextcloud-mcp-server.git
   cd nextcloud-mcp-server
   

2. Install the package (if running as a library):

   poetry install
   

Docker Installation

A pre-built Docker image is available on ghcr.io:

docker run -p 127.0.0.1:8000:8000 --env-file .env --rm ghcr.io/cbcoutinho/nextcloud-mcp-server:latest

💡 Key Use Cases in AI Workflows

Use Case 1: Automating Note Creation and Management

A financial analyst uses the Nextcloud MCP Server to create a new note with an important meeting summary:

• AI Application: Claude Desktop
• Workflow:
  • The analyst triggers nc_notes_create_note through their LLM interface.
  • This creates a detailed report on the meeting outcomes, categorized under the relevant project notes.

Use Case 2: Updating and Deleting Notes for Task Management

A developer regularly updates task progress within Nextcloud using the following commands:

• AI Application: Continue
• Workflow:
  • The developer uses nc_notes_update_note to log completed tasks.
  • They also use nc_notes_delete_note to remove outdated notes as they are resolved.

🔌 Integration with MCP Clients

To integrate the Nextcloud MCP Server with AI applications, follow these steps:

1. Add Server via MCP Client:

   uvx mcp add nextcloud-mcp http://localhost:8000 --default-transport sse
   

2. Invoke APIs from LLM Interface: Connect your preferred LLM tool (like Claude Desktop or Continue) to uvx and invoke the necessary MCP commands.

📊 Performance & Compatibility Matrix

The Nextcloud MCP Server is compatible with multiple MCP clients, ensuring broad utility across different AI applications:

MCP Client	Resources	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅	✅	✅
Cursor	❌	✅	❌

This compatibility matrix highlights the extensive support for resource management and tool integration, while limiting prompt functionalities to selected clients.

🛠️ Advanced Configuration & Security

Environment Variables

Ensure sensitive information is safely stored by creating an .env file based on env.sample:

NEXTCLOUD_HOST=https://your.nextcloud.instance.com
NEXTCLOUD_USERNAME=your_nextcloud_username
NEXTCLOUD_PASSWORD=your_nextcloud_app_password_or_login_password

Security Best Practices

• Use a dedicated Nextcloud App Password for enhanced security.
• Regularly update your Nextcloud version to protect against vulnerabilities.

❓ Frequently Asked Questions (FAQ)

1. Question: Can I use my regular login password instead of an App Password?
   • Answer: It is strongly recommended to use a dedicated App Password, as it enhances security by isolating access to specific applications.
2. Question: How do I set up the server for remote usage?
   • Answer: For remote access, ensure your .env file contains public endpoints and configure firewalls accordingly to allow secure connections.
3. Question: Are there any limitations on concurrent API calls?
   • Answer: The Nextcloud MCP Server handles multiple requests efficiently. While no explicit limit is mentioned in the README, best practices suggest monitoring performance to avoid overload.
4. Question: Can I create custom APIs beyond what's provided by the Notes API?
   • Answer: Yes, you can extend the functionality using the Python SDK linked in the repository documentation.
5. Question: How do I contribute or report issues with the server?
   • Answer: Contributing is welcome! Submit issues on GitHub or suggest pull requests to improve the codebase.

👨‍💻 Development & Contribution Guidelines

Contributions are highly valued and can be submitted through the following steps:

1. Clone the repository.
2. Fork the project on GitHub.
3. Contribute your changes or report bugs.
4. Submit a Pull Request explaining your changes.

🌐 MCP Ecosystem & Resources

The Nextcloud MCP Server is part of a larger ecosystem that includes other tools and resources:

• GitHub Repository: https://github.com/cbcoutinho/nextcloud-mcp-server
• MCP SDK Documentation: https://github.com/modelcontextprotocol/python-sdk

By leveraging these resources, developers can build robust AI applications that integrate seamlessly with Nextcloud and other data management solutions.

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This comprehensive documentation emphasizes the versatility and integration capabilities of the Nextcloud MCP Server. It is designed for developers looking to enhance their AI workflows by connecting LLMs to Nextcloud through the Model Context Protocol (MCP).