MiniMax Vision MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| MINIMAX_MODEL | No | Model: MiniMax-M3, MiniMax-M2.7, MiniMax-M2.7-highspeed, MiniMax-M2.5, MiniMax-M2.5-highspeed, MiniMax-M2.1, MiniMax-M2.1-highspeed, MiniMax-M2. | MiniMax-M3 |
| MINIMAX_API_KEY | Yes | Your MiniMax API key. | |
| MINIMAX_BASE_URL | No | Override endpoint (for proxies). | https://api.minimax.chat/v1 |
| MINIMAX_MAX_TOKENS | No | Default max output tokens. M3 supports up to 524288. | 8192 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| minimax_vision_understandA | Analyze an image using MiniMax vision models. Supports local image files (png/jpg/jpeg/gif/webp/bmp) AND remote HTTP(S) URLs. Default model: MiniMax-M3. MiniMax-M3 supports image + video understanding, 1M context, adaptive thinking. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of confusing it with another. The tool's purpose is clearly defined for image understanding.
The single tool name 'minimax_vision_understand' follows a clear verb_noun pattern, and with only one tool, naming consistency is trivially perfect.
A single tool feels thin for a server named 'Vision MCP Server', but it covers the core image understanding use case. It is borderline but not severely under-scoped.
The tool covers basic image understanding and supports multiple input formats, but lacks options for model selection or video understanding, despite the underlying model supporting video. Some common vision tasks like OCR or object detection are not present, but that may be out of scope.