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Minio MCP Service

Minio MCP Service

Local
github.com/ucesysFiles & Storage6Updated 84w ago

About Minio MCP Service

Minio MCP Service is a Python MCP server and client for MinIO object storage. It exposes bucket and object operations and object data to MCP clients, with basic and Anthropic-based client implementations.

Key features

  1. 01List buckets and objects
  2. 02Retrieve and upload objects
  3. 03Expose text and binary files as resources
  4. 04Provide bucket contents as resources
  5. 05Include basic and Anthropic clients

Use cases

  1. 01Browse buckets and filter objects by prefix
  2. 02Retrieve or upload an object in MinIO
  3. 03Access file contents through MCP resources

MCP support

The server exposes MinIO buckets and objects through MCP tools and resources. The project also includes basic and Anthropic clients for interacting with the server.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MinIO Model-Context Protocol (MCP)

This project implements a Model-Context Protocol (MCP) server and client for MinIO object storage. It provides a standardized way to interact with MinIO.

Features

Server
Resources

Exposes MinIO data through Resources. The server can access and provide:

  • Text files (automatically detected based on file extension)
  • Binary files (handled as application/octet-stream)
  • Bucket contents (up to 1000 objects per bucket)
Tools
  • ListBuckets

    • Returns a list of all buckets owned by the authenticated sender of the request
    • Optional parameters: start_after (pagination), max_buckets (limit results)
  • ListObjects

    • Returns some or all (up to 1,000) of the objects in a bucket with each request
    • Required parameter: bucket_name
    • Optional parameters: prefix (filter by prefix), max_keys (limit results)
  • GetObject

    • Retrieves an object from MinIO
    • Required parameters: bucket_name, object_name
  • PutObject

    • Uploads a file to MinIO bucket using fput method
    • Required parameters: bucket_name, object_name, file_path
Client

The project includes multiple client implementations:

  1. Basic Client - Simple client for direct interaction with the MinIO MCP server
  2. Anthropic Client - Integration with Anthropic's Claude models for AI-powered interactions with MinIO

Installation

  1. Clone the repository:
git clone https://github.com/yourusername/minio-mcp.git
cd minio-mcp
  1. Install dependencies using pip:
pip install -r requirements.txt

Or using uv:

uv pip install -r requirements.txt

Environment Configuration

Create a .env file in the root directory with the following configuration:

# MinIO Configuration
MINIO_ENDPOINT=play.min.io
MINIO_ACCESS_KEY=your_access_key
MINIO_SECRET_KEY=your_secret_key
MINIO_SECURE=true
MINIO_MAX_BUCKETS=5

# Server Configuration
SERVER_HOST=0.0.0.0
SERVER_PORT=8000

# For Anthropic Client (if using)
ANTHROPIC_API_KEY=your_anthropic_api_key

Usage

Running the Server

The server can be run directly:

python src/minio_mcp_server/server.py
Using the Basic Client
from src.client import main
import asyncio

asyncio.run(main())
Using the Anthropic Client
  1. Configure the servers in src/client/servers_config.json:
{
  "mcpServers": {
    "minio_service": {
      "command": "python",
      "args": ["path/to/minio_mcp_server/server.py"]
    }
  }
}
  1. Run the client:
python src/client/mcp_anthropic_client.py
  1. Interact with the assistant:

    • The assistant will automatically detect available tools
    • You can ask questions about your MinIO data
    • The assistant will use the appropriate tools to retrieve information
  2. Exit the session:

    • Type quit or exit to end the session

Integration with Claude Desktop

You can integrate this MCP server with Claude Desktop:

Configuration

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "minio-mcp": {
      "command": "python",
      "args": [
        "path/to/minio-mcp/src/minio_mcp_server/server.py"
      ]
    }
  }
}

Development

Project Structure
minio-mcp/
├── src/
│   ├── client/                  # Client implementations
│   │   ├── mcp_anthropic_client.py  # Anthropic integration
│   │   └── servers_config.json  # Server configuration
│   ├── minio_mcp_server/        # MCP server implementation
│   │   ├── resources/           # Resource implementations
│   │   │   └── minio_resource.py  # MinIO resource
│   │   └── server.py            # Main server implementation
│   ├── __init__.py
│   └── client.py                # Basic client implementation
├── LICENSE
├── pyproject.toml
├── README.md
└── requirements.txt
Running Tests
pytest
Code Formatting
black src/
isort src/
flake8 src/

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we recommend using the MCP Inspector:

npx @modelcontextprotocol/inspector python path/to/minio-mcp/src/minio_mcp_server/server.py

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Comments

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