Opencode MiniMax Easy Vision

MiniMax Easy Vision is a plugin for OpenCode that enables vision support for models that lack native image attachment support.

Originally built for MiniMax models, it can be configured to work with any model that requires MCP-based image handling.

It restores the "paste and ask" workflow by automatically saving image assets and routing them through the MiniMax Coding Plan MCP

Table of Contents

• Demo
• The Problem
• Prerequisites
• Installation
  • Via npm
  • From Local Source
• What This Plugin Does
• Supported Models
  • Custom Model Configuration
    • Locations (Priority Order)
    • Config Format
    • Pattern Syntax
    • Wildcard Rules
    • Configuration Examples
  • Custom Image Analysis Tool
• Supported Image Formats
• Usage
  • Example Interaction
• Development
• License
• References

Demo

See how it works:

https://github.com/user-attachments/assets/df396c6c-6fa8-46b8-8984-c003ecf1c12c

https://github.com/user-attachments/assets/826f90ea-913f-427e-ace8-0b711302c497

The Problem

When using MiniMax models (like MiniMax M2.1) in OpenCode, native image attachments aren't supported.

These models expect the MiniMax Coding Plan MCP's understand_image tool, which requires an explicit file path. This breaks the normal flow:

• Ignored images: Pasted images are simply ignored by the model.
• Manual steps: You have to save screenshots manually, find the path, and reference it in your prompt.
• Broken flow: The "paste and ask" experience available with Claude or GPT models is lost.

Prerequisites

The MiniMax Coding Plan MCP server must be configured in your opencode.json:

{
  "mcp": {
    "MiniMax": {
      "command": "uvx",
      "args": ["minimax-coding-plan-mcp"],
      "env": {
        "MINIMAX_API_KEY": "your-api-key-here",
        "MINIMAX_API_HOST": "https://api.minimax.io"
      }
    }
  }
}

Installation

Via npm

Just add the plugin to the plugin array in your opencode.json file:

{
  "$schema": "https://opencode.ai/config.json",
  "plugin": ["opencode-minimax-easy-vision"]
}

From Local Source

1. Clone the repository.
2. Build the plugin:

   npm install && npm run build

3. Copy the built dist/index.js into your OpenCode plugin directory.

What This Plugin Does

This plugin automates the vision pipeline so you don't have to think about it.

How it works:

1. Detects when a configured model is active.
2. Intercepts images pasted into the chat.
3. Saves them to a temporary local directory.
4. Injects the necessary context for the model to invoke the understand_image tool with the correct path.

Result: You just paste the image and ask your question just like how you do with Claude or GPT models. The plugin handles the rest.

Supported Models

By default, the plugin activates for MiniMax models:

• Provider ID containing minimax
• Model ID containing minimax or abab

Examples:

• minimax/minimax-m2.1
• minimax/abab6.5s-chat

Custom Model Configuration

You can enable this for other models by creating a config file.

Locations (Priority Order)

1. Project level: .opencode/opencode-minimax-easy-vision.json
2. User level: ~/.config/opencode/opencode-minimax-easy-vision.json

Config Format

{
  "models": ["minimax/*", "opencode/*", "*/glm-4.7-free"]
}

Pattern Syntax

| Pattern | Matches | | ---------------- | --------------------------------------- | | * | Match ALL models | | minimax/* | All models from the minimax provider | | */glm-4.7-free | Specific model from any provider | | opencode/* | All models from the opencode provider | | */abab* | Any model containing abab |

Wildcard Rules

• *suffix matches values ending with suffix
• prefix* matches values starting with prefix
• * matches everything
• *text* matches values containing text

If the config is missing or empty, it defaults to MiniMax-only behavior.

Configuration Examples

Enable for all models:

{
  "models": ["*"]
}

Specific providers:

{
  "models": ["minimax/*", "opencode/*", "google/*"]
}

Mix of providers and models:

{
  "models": ["minimax/*", "opencode/gpt-5-nano", "*/claude-3-7-sonnet*"]
}

Custom Image Analysis Tool

By default, the plugin uses the mcp_minimax_understand_image tool from the MiniMax Coding Plan MCP. You can configure a different tool for image analysis:

{
  "models": ["*"],
  "imageAnalysisTool": "mcp_openrouter_analyze_image"
}

[!NOTE] The imageAnalysisTool value is the tool name, not the MCP server name.

MCP servers expose one or more tools—for example, the MiniMax Coding Plan MCP server exposes the mcp_minimax_understand_image tool.

This allows you to use tools from other MCP servers that provide image analysis capabilities, such as:

• openrouter-image-mcp - Uses OpenRouter with GPT-4V, Claude, Gemini
• mcp-image-recognition - Uses Anthropic/OpenAI Vision APIs
• Peekaboo - macOS screenshot + AI analysis

The plugin will instruct the model to use the configured tool. The tool should accept an image file path as input.

Supported Image Formats

• PNG
• JPEG
• WebP

(Limited by the MiniMax Coding Plan MCP understand_image tool.)

Usage

1. Select a supported model in OpenCode.
2. Paste an image (Cmd+V / Ctrl+V).
3. Ask a question about it, just like how you do for other models with native vision support.

Example Interaction

You: [pasted screenshot] Why is this failing?

Model: I'll check the image using the understand_image tool. [Calls mcp_minimax_understand_image path="/tmp/xyz.png"]

Model: The error suggests a syntax error on line 12.

Development

npm install
npm run build

The built plugin will be available at dist/index.js

License

AGPL-3.0. See LICENSE

References

• OpenCode Official Website
• OpenCode Plugins Documentation
• MiniMax Official Website
• MiniMax Coding Plan MCP Repository
• MiniMax API Documentation