MCP Server Box

MCP Server Box avatar

by box-community

Official Integrations

An MCP server capable of interacting with the Box API

What is MCP Server Box

MCP Server Box

Description

MCP Server Box is a Python project that integrates with the Box API to perform various operations such as file search, text extraction, AI-based querying, and data extraction. It leverages the box-sdk-gen library and provides a set of tools to interact with Box files and folders.

The Model Context Protocol (MCP) is a framework designed to standardize the way models interact with various data sources and services. In this project, MCP is used to facilitate seamless integration with the Box API, enabling efficient and scalable operations on Box files and folders. The MCP Server Box project aims to provide a robust and flexible solution for managing and processing Box data using advanced AI and machine learning techniques.

Tools implemented

Box Tools

box_who_am_i

Get your current user information and check connection status.

Returns: User information string

box_authorize_app_tool

Start the Box application authorization process.

Returns: Authorization status message

box_search_tool

Search for files in Box.

Parameters:

  • query (str): Search query
  • file_extensions (List[str], optional): File extensions to filter by
  • where_to_look_for_query (List[str], optional): Where to search (NAME, DESCRIPTION, FILE_CONTENT, COMMENTS, TAG)
  • ancestor_folder_ids (List[str], optional): Folder IDs to search within

Returns: Search results

box_read_tool

Read the text content of a Box file.

Parameters:

  • file_id (str): ID of the file to read

Returns: File content

box_ask_ai_tool

Ask Box AI about a file.

Parameters:

  • file_id (str): ID of the file
  • prompt (str): Question for the AI

Returns: AI response

box_search_folder_by_name

Locate a folder by name.

Parameters:

  • folder_name (str): Name of the folder

Returns: Folder ID

box_ai_extract_data

Extract data from a file using AI.

Parameters:

  • file_id (str): ID of the file
  • fields (str): Fields to extract

Returns: Extracted data in JSON format

box_list_folder_content_by_folder_id

List folder contents.

Parameters:

  • folder_id (str): ID of the folder
  • is_recursive (bool): Whether to list recursively

Returns: Folder content in JSON format with id, name, type, and description

box_manage_folder_tool

Create, update, or delete folders in Box.

Parameters:

  • action (str): Action to perform: "create", "delete", or "update"
  • folder_id (str, optional): ID of the folder (required for delete/update)
  • name (str, optional): Folder name (required for create, optional for update)
  • parent_id (str, optional): Parent folder ID (required for create, optional for update)
  • description (str, optional): Folder description (optional for update)
  • recursive (bool, optional): Whether to delete recursively (optional for delete)

Returns: Status message with folder details

box_upload_file_tool

Upload content as a file to Box.

Parameters:

  • content (str): The content to upload as a file
  • file_name (str): The name to give the file in Box
  • folder_id (Any, optional): The ID of the folder to upload to

Returns: Upload status with file ID and name

box_download_file_tool

Download a file from Box and return its content.

Parameters:

  • file_id (Any): The ID of the file to download
  • save_file (bool, optional): Whether to save the file locally
  • save_path (str, optional): Path where to save the file

Returns: File content as text, base64-encoded image, or save status message

Requirements

  • Python 3.13 or higher
  • Box API credentials (Client ID, Client Secret, etc.)

Installation

  1. Clone the repository:

    git clone https://github.com/box-community/mcp-server-box.git
    cd mcp-server-box
    
  2. Install uv if not installed yet:

    2.1 MacOS+Linux

    curl -LsSf https://astral.sh/uv/install.sh | sh
    

    2.2 Windows

    powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
    
  3. Create and set up our project:

    3.1 MacOS+Linux

    # Create virtual environment and activate it
    uv venv
    source .venv/bin/activate
    
    # Lock the dependencies
    uv lock
    

    3.1 Windows

    # Create virtual environment and activate it
    uv venv
    .venv\Scripts\activate
    
    # Lock the dependencies
    uv lock
    
  4. Create a .env file in the root directory and add your Box API credentials:

    BOX_CLIENT_ID=your_client_id
    BOX_CLIENT_SECRET=your_client_secret
    

Usage

Running the MCP Server

To start the MCP server, run the following command:

uv --directory /Users/anovotny/Desktop/mcp-server-box run src/mcp_server_box.py

Using Claude as the client

  1. Edit your claude_desktop_config.json
code ~/Library/Application\ Support/Claude/claude_desktop_config.json
  1. And add the following:
{
    "mcpServers": {
        "mcp-server-box": {
            "command": "uv",
            "args": [
                "--directory",
                "/Users/anovotny/Desktop/mcp-server-box",
                "run",
                "src/mcp_server_box.py"
            ]
        }
    }
}
  1. If CLaude is running restart it

## Running Tests

The project includes a suite of tests to verify Box API functionality. Before running the tests, you'll need to update the file and folder IDs in the test files to match files in your Box account.

### Setting Up Tests

1. **Update File and Folder IDs**: 
   - Each test file (in the `tests/` directory) contains hardcoded IDs for Box files and folders
   - You need to replace these IDs with IDs of files and folders in your Box account
   - Example: In `test_box_api_read.py`, replace `"1728677291168"` with the ID of a file in your Box account

2. **Test File ID References**:
   - `test_box_api_read.py`: Needs a valid document file ID (e.g., a Word document)
   - `test_box_api_search.py`: Update the search queries and file extensions to match your content
   - `test_box_api_ai.py`: Needs a file ID for testing AI extraction capabilities
   - Other test files may require specific folder IDs or file types

### Running Tests

Once you've updated the file IDs, you can run tests using pytest:

```bash
# Run all tests
pytest

# Run a specific test file
pytest tests/test_box_api_file_ops.py

# Run tests with detailed output
pytest -v

# Run tests and show print statements
pytest -v -s

Available Tests

  • test_box_auth.py: Tests authentication functionality
  • test_box_api_basic.py: Basic Box API tests
  • test_box_api_read.py: Tests file reading capabilities
  • test_box_api_search.py: Tests search functionality
  • test_box_api_ai.py: Tests AI-based features
  • test_box_api_file_ops.py: Tests file upload and download operations

Creating New Tests

When creating new tests:

  1. Follow the pattern in existing test files
  2. Use the box_client fixture for authenticated API access
  3. Clean up any test files or folders created during tests
  4. Add proper assertions to verify functionality

Troubleshooting

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.