Minio MCP Python Implementation
Minio MCP Service MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Minio MCP Python Implementation.
This project implements a Model-Context Protocol (MCP) server and client for MinIO object storage. It provides a standardized way to interact with MinIO.
Once Minio MCP Service is connected, these are the calls the assistant has available:
Server — The Server tool exposed by this serverResources — Exposes MinIO data through Resources. The server can access and provide: - Text files (automatically detected based on file extension) - BinaryTools — The Tools tool exposed by this serverClient — 1. Basic Client - Simple client for direct interaction with the MinIO MCP server 2. Anthropic Client - Integration with Anthropic's ClaudeConfiguration — The Configuration tool exposed by this serverInstallation goes through your MCP client rather than a global install: point it at @modelcontextprotocol/inspector on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
You will need 4 environment variables: MINIO_ACCESS_KEY, MINIO_SECRET_KEY, SERVER_HOST, ANTHROPIC_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Minio MCP Service's toolset — Server, Resources, Tools and 2 more — is a fair guide to whether it matches your workflow. It is maintained by ucesys; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| Server | The Server tool exposed by this 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 100 |
| Tools | The Tools tool exposed by this server. |
| Client | 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 |
| Configuration | The Configuration tool exposed by this server. |
{
"mcpServers": {
"minio_service": {
"command": "python",
"args": ["path/to/minio_mcp_server/server.py"]
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| MINIO_ACCESS_KEY | Credential the server authenticates with. | Yes |
| MINIO_SECRET_KEY | Credential the server authenticates with. | Yes |
| SERVER_HOST | Endpoint or connection string the server talks to. | Optional |
| ANTHROPIC_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.