# ViperGPT Visual Question Answering

> Use this tool when you need to analyze images and answer complex questions about visual content, such as object detection and multi-step visual reasoning. It solves problems like image analysis, natural language queries, and compositional question answering by combining multiple AI models to provide accurate results. The tool takes in images and natural language queries as inputs and generates answers as outputs, making it ideal for applications requiring advanced visual reasoning capabilities.

Canonical page: https://skillsregistry.net/skills/vipergpt-visual-qa  
JSON: https://api.skillsregistry.net/v1/skills/vipergpt-visual-qa

## Description

ViperMCP server implementation by Ryan Sherby that provides visual question-answering capabilities through a mixture-of-experts approach based on the ViperGPT framework. The implementation combines multiple AI models including Grounding DINO, SegmentAnything, GPT-4o variants, X-VLM, MiDaS, and BERT to handle three core task areas: visual grounding, compositional image question answering, and external knowledge-dependent image question answering. Built as a FastMCP streamable-http server with Docker support and Smithery deployment options, it generates and executes Python code to solve complex visual reasoning tasks, making it valuable for applications requiring advanced image analysis, object detection with natural language queries, and multi-step visual reasoning workflows.

## Trust

- **Trust score (0–1):** 0.32
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/vipergpt-visual-qa)
- **Repository:** <https://github.com/ryansherby/vipermcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "vipergpt-visual-qa"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vipergpt-visual-qa` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vipergpt-visual-qa/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt