# Hybrid Vision MCP Server

> Hybrid Vision MCP Server — sameersemna-hybrid-vision-mcp. Use this tool when you need to analyze and compare images, extract text, or annotate browser screenshots, and require a bridge between local vision engines and cloud-based vision models over a standardized transport protocol. It solves problems related to image analysis, text localization, and comparison, and accepts image files or browser screenshots as input, producing annotated outputs. It is particularly useful in applications where local processing and cloud-based AI models need to be integrated for enhanced vision capabilities.

Canonical page: https://skillsregistry.net/skills/sameersemna-hybrid-vision-mcp  
JSON: https://api.skillsregistry.net/v1/skills/sameersemna-hybrid-vision-mcp

## Description

Bridges local vision engines (Tesseract.js OCR and Sharp preprocessing) with Ollama vision models for image analysis, comparison, text localization, and browser screenshot annotation over MCP-compliant HTTP/SSE transports.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** browser-automation
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/iiwvu20uo4)
- **Repository:** <https://github.com/sameersemna/hybrid-vision-mcp>

## 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": "sameersemna-hybrid-vision-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sameersemna-hybrid-vision-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sameersemna-hybrid-vision-mcp/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