What can you do with this server?

This server provides AI-powered multimodal understanding of images, audio, and video using the Xiaomi MiMo API. It exposes three tools: * Image Understanding (understand_image): Analyze single or multiple images via URL, local path, or base64. Supports JPEG, PNG, GIF, WebP (up to 10MB). Configurable prompt, system prompt, and max output tokens. * Audio Understanding (understand_audio): Transcribe or analyze single or multiple audio files via URL or local path. Supports MP3, WAV, FLAC, M4A, OGG (URL: up to 100MB, Base64: up to 50MB). Configurable prompt, system prompt, and max output tokens. * Video Understanding (understand_video): Analyze single or multiple video files via URL or local path. Supports MP4, MOV, AVI, WMV (URL: up to 300MB, Base64: up to 50MB). Configurable frames-per-second (range: 0.1–10, default: 2), media resolution (default or max), system prompt, and max output tokens.

Which integrations are available for this server?

Provides tools for analyzing images, audio, and video using Xiaomi MiMo's multimodal understanding API, supporting multiple input formats and customization options like fps and resolution for video.

How do I use MiMo Multimodal Understanding MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MiMo Multimodal Understanding MCP Server What's in this image? https://example.com/photo.jpg" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MiMo Multimodal Understanding MCP Server

by ChanthMiao

Overview Schema Related Servers Score Discussions

Python

Remote

MiMo Multimodal Understanding MCP Server

MCP server for Xiaomi MiMo multimodal understanding API (image, audio, video).

Features

Image Understanding: Single/multiple images, URL and local file support
Audio Understanding: Single/multiple audio, URL and local file support
Video Understanding: Single/multiple video, URL and local file support, configurable fps and resolution

Related MCP server: Vision MCP

Setup

1. Install dependencies

uv sync

2. Configure API Key

Copy .env.example to .env and fill in your API key:

cp .env.example .env

Or set environment variable directly:

export MIMO_API_KEY=your_api_key_here

Get your API key from: https://platform.xiaomimimo.com

3. (Optional) Configure API Base URL

The default API endpoint is determined by your API key prefix:

Key Prefix	Default Endpoint
`tp-*`	`https://token-plan-cn.xiaomimimo.com/v1`
`sk-*` or others	`https://api.xiaomimimo.com/v1`

To use a different API endpoint:

export MIMO_API_BASE=https://your-custom-endpoint/v1

Or add it to your .env file:

MIMO_API_BASE=https://your-custom-endpoint/v1

Usage

Quick Start (with uvx)

export MIMO_API_KEY=your_api_key_here
uvx mimo-multimodal-mcp

Development mode (with MCP Inspector)

uv run mcp dev src/mimo_multimodal_mcp/server.py

Install to Claude Desktop

uv run mcp install src/mimo_multimodal_mcp/server.py

Direct execution

uv run python src/mimo_multimodal_mcp/server.py

Claude Desktop Configuration

Add to ~/.config/claude/claude_desktop_config.json:

{
  "mcpServers": {
    "mimo-multimodal": {
      "command": "uvx",
      "args": ["mimo-multimodal-mcp"],
      "env": {
        "MIMO_API_KEY": "your_api_key_here"
      }
    }
  }
}

Tools

`understand_image`

Analyze images using Xiaomi MiMo multimodal model.

Parameter	Type	Required	Description
`prompt`	string	Yes	Image understanding task description
`image_url`	string	No	Single image URL or data:image base64
`image_path`	string	No	Single local image file path
`image_urls`	list[string]	No	Multiple image URLs
`image_paths`	list[string]	No	Multiple local image file paths
`system_prompt`	string	No	Custom system prompt
`max_tokens`	integer	No	Max output length (default: 8192, max: 32768)

Supported formats: JPEG, PNG, GIF, WebP Size limit: 10MB

`understand_audio`

Analyze audio using Xiaomi MiMo multimodal model.

Parameter	Type	Required	Description
`prompt`	string	Yes	Audio understanding task description
`audio_url`	string	No	Single audio URL
`audio_path`	string	No	Single local audio file path
`audio_urls`	list[string]	No	Multiple audio URLs
`audio_paths`	list[string]	No	Multiple local audio file paths
`system_prompt`	string	No	Custom system prompt
`max_tokens`	integer	No	Max output length (default: 8192, max: 32768)

Supported formats: MP3, WAV, FLAC, M4A, OGG Size limit: URL 100MB, Base64 50MB

`understand_video`

Analyze video using Xiaomi MiMo multimodal model.

Parameter	Type	Required	Description
`prompt`	string	Yes	Video understanding task description
`video_url`	string	No	Single video URL
`video_path`	string	No	Single local video file path
`video_urls`	list[string]	No	Multiple video URLs
`video_paths`	list[string]	No	Multiple local video file paths
`fps`	float	No	Frames per second, range [0.1, 10], default: 2
`media_resolution`	string	No	Resolution: "default" or "max"
`system_prompt`	string	No	Custom system prompt
`max_tokens`	integer	No	Max output length (default: 8192, max: 32768)

Supported formats: MP4, MOV, AVI, WMV Size limit: URL 300MB, Base64 50MB

Examples

Image Understanding

# URL
await understand_image(prompt="Describe this image", image_url="https://example.com/image.jpg")

# Local file
await understand_image(prompt="What text is in this?", image_path="/path/to/screenshot.png")

# Multiple images
await understand_image(prompt="Compare these", image_urls=["url1", "url2"])

Audio Understanding

# URL
await understand_audio(prompt="Transcribe this audio", audio_url="https://example.com/audio.wav")

# Local file
await understand_audio(prompt="What is being said?", audio_path="/path/to/audio.mp3")

Video Understanding

# URL with default settings
await understand_video(prompt="Describe this video", video_url="https://example.com/video.mp4")

# URL with custom fps and resolution
await understand_video(
    prompt="Describe the action",
    video_url="https://example.com/video.mp4",
    fps=5.0,
    media_resolution="max"
)

Install Server

license - not found

quality

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

0dRelease cycle

4Releases (12mo)

Commit activity

Resources

GitHub Repository

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