Which integrations are available for this server?

Enables cloud-based vision analysis via Google Gemini models, including free tier access. Provides local, private AI vision analysis using Ollama models, enabling image understanding without sending data to external servers. Enables high-quality vision analysis via OpenAI models like GPT-4o.

How do I use OpenSight MCP?

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., "@OpenSight MCP analyze the screenshot on my clipboard" 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.

OpenSight MCP

by Mr-JoE1

Overview Schema Related Servers Score Discussions

JavaScript

Hybrid

👁️ OpenSight MCP

npm version Node.js License: MIT MCP

Multi-backend AI vision for MCP agents. Analyze images, screenshots, and documents using local Ollama models (private, uncensored) or cloud APIs (OpenAI, Google Gemini, OpenRouter). Works with any MCP-compatible coding agent.

Quick Start

npx opensight-mcp@latest

	Best for	Install
Local & Private	Privacy-first, uncensored, no API keys	`ollama pull minicpm-v:latest`
Free Tier APIs	Zero-cost cloud vision via Google/OpenRouter	Set `GOOGLE_API_KEY` or `OPENROUTER_API_KEY`
Paid APIs	OpenAI GPT-4o, Claude Vision, any OpenAI-compatible	Set `OPENAI_API_KEY`

Related MCP server: image-mcp

🎯 Why OpenSight?

Local & Private	Free Tiers	Multi-Vendor	Agent-Native
Ollama runs on your hardware. No data leaves your network. Uncensored models.	Google Gemini Flash and OpenRouter offer free vision tiers. Zero cost to start.	One tool, any backend. Swap providers with an env var — no code changes.	Purpose-built for MCP agents. Clipboard, file paths, URLs, base64 — all supported.

📦 Installation

Standard config (all MCP clients)

{
  "mcpServers": {
    "opensight": {
      "command": "npx",
      "args": ["opensight-mcp@latest"],
      "env": {
        "OLLAMA_HOST": "127.0.0.1:11434",
        "VISION_MODEL": "minicpm-v:latest"
      }
    }
  }
}

Add to ~/.config/opencode/opencode.jsonc:

{
  "mcp": {
    "opensight": {
      "type": "local",
      "command": ["npx", "opensight-mcp@latest"],
      "enabled": true,
      "env": {
        "OLLAMA_HOST": "192.168.46.34",
        "VISION_MODEL": "minicpm-v:latest"
      }
    }
  }
}

claude mcp add opensight npx opensight-mcp@latest

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "opensight": {
      "command": "npx",
      "args": ["opensight-mcp@latest"],
      "env": {
        "OLLAMA_HOST": "127.0.0.1:11434",
        "VISION_MODEL": "minicpm-v:latest"
      }
    }
  }
}

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "opensight": {
      "command": "npx",
      "args": ["opensight-mcp@latest"]
    }
  }
}

code --add-mcp '{"name":"opensight","command":"npx","args":["opensight-mcp@latest"]}'

Use the standard config above. Same pattern for all MCP-compatible clients.

Add to ~/.hermes/config.yaml:

mcp_servers:
  opensight:
    command: "npx"
    args: ["-y", "opensight-mcp@latest"]
    env:
      OLLAMA_HOST: "127.0.0.1:11434"
      VISION_MODEL: "minicpm-v:latest"

Then reload:

/reload-mcp

Verify it's loaded:

Tell me which MCP-backed tools are available right now.

Manual install (for development)

git clone https://github.com/Mr-JoE1/opensight-mcp.git
cd opensight-mcp
npm install
npm test

🛠️ Tools

vision.analyze_image — General-purpose image analysis. Accepts data URIs (clipboard paste), base64, URLs, or file paths. Configurable system prompt, model, temperature.
vision.describe — UI/QA-focused screenshot analysis. Defaults to a QA system prompt that identifies errors, warnings, and layout issues.
vision.clipboard — Read and analyze images directly from the OS clipboard. Uses clipboardy for cross-platform support (macOS/Windows built-in, Linux needs xclip/wl-clipboard).
vision.find_images — Scan common directories (~/Downloads, ~/Pictures, /tmp) for recently modified images. Zero dependencies — pure Node.js fs.

vision.ocr — Extract text from images using VLM or Tesseract OCR. Supports structured JSON output with text block types.
vision.find_text — Locate specific text in an image with bounding box coordinates. Supports fuzzy matching.

vision.warmup — Pre-load the vision model into GPU VRAM to eliminate cold-start latency.
vision.health — Check backend connection status and list available models.

🔌 Backends

Configure via environment variables. The default is Ollama (local, no API keys needed).

Provider	Env Var	Free Tier	Best For
Ollama	`OLLAMA_HOST`	✅ (your hardware)	Privacy, uncensored, offline
Google Gemini	`GOOGLE_API_KEY`	✅ (Flash 2.0)	Free tier, high accuracy
OpenRouter	`OPENROUTER_API_KEY`	✅ (qwen-vl free)	Multi-model, free tier
OpenAI	`OPENAI_API_KEY`	❌	GPT-4o, best quality

Set the active provider:

# Use Google Gemini (free tier)
export VISION_PROVIDER=google
export GOOGLE_API_KEY=your_key_here

# Use OpenAI (paid)
export VISION_PROVIDER=openai
export OPENAI_API_KEY=sk-...

# Use OpenRouter (free qwen-vl)
export VISION_PROVIDER=openrouter
export OPENROUTER_API_KEY=your_key_here

# Default: Ollama (local)
export OLLAMA_HOST=192.168.46.34:11434

⚙️ Configuration

All settings via environment variables:

Variable	Default	Description
`VISION_ENDPOINT`	`local`	Endpoint mode: `local` (OLLAMA_HOST/PORT) or `global` (OLLAMA_GLOBAL_HOST/PORT)
`OLLAMA_HOST`	`192.168.46.34`	Ollama server host (local endpoint)
`OLLAMA_PORT`	`11434`	Ollama API port (local endpoint)
`OLLAMA_GLOBAL_HOST`	`192.168.46.34`	Ollama server host (global/WAN endpoint)
`OLLAMA_GLOBAL_PORT`	`11434`	Ollama API port (global/WAN endpoint)
`VISION_MODEL`	`minicpm-v:latest`	Default vision model
`OCR_MODEL`	`minicpm-v:latest`	Default OCR model
`VISION_PROVIDER`	`ollama`	Backend: ollama, openai, google, openrouter
`OPENAI_API_KEY`	—	OpenAI API key
`GOOGLE_API_KEY`	—	Google Gemini API key
`OPENROUTER_API_KEY`	—	OpenRouter API key
`MAX_TOKENS`	`2048`	Max response tokens
`VISION_WARMUP_ON_START`	`1`	Auto-warmup model on server start
`VISION_KEEP_ALIVE`	`10m`	Model keep-alive duration
`VISION_TIMEOUT_MS`	`120000`	Request timeout (ms)
`VISION_MAX_RETRIES`	`3`	Retry attempts on failure

Local vs Global Endpoints

Toggle between LAN and WAN endpoints with VISION_ENDPOINT:

Local (default):

export VISION_ENDPOINT=local
export OLLAMA_HOST=192.168.46.34
export OLLAMA_PORT=11434

Global (DDNS/WAN):

export VISION_ENDPOINT=global
export OLLAMA_GLOBAL_HOST=ih-tatweer.duckdns.org
export OLLAMA_GLOBAL_PORT=13313

OpenCode example with both endpoints configured:

{
  "mcp": {
    "vision": {
      "type": "local",
      "command": ["node", "/path/to/vision-mcp.mjs"],
      "env": {
        "VISION_ENDPOINT": "local",
        "OLLAMA_HOST": "192.168.46.34",
        "OLLAMA_PORT": "11434",
        "OLLAMA_GLOBAL_HOST": "ih-tatweer.duckdns.org",
        "OLLAMA_GLOBAL_PORT": "13313",
        "VISION_MODEL": "minicpm-v:latest"
      }
    }
  }
}

🏃 CLI Usage

# Health check
npx opensight-mcp health
# or
vlm health

# Analyze an image
vlm describe --image screenshot.png --prompt "What errors are visible?"

# Extract text (OCR)
vlm ocr --image document.png --engine vlm

# Find text with coordinates
vlm find --image app.png --query "Submit button"

🤖 Recommended Models

Model	Size	Best For
`minicpm-v:latest`	~5.5 GB	Default. General analysis, OCR, UI. Fast and accurate.
`llava:7b`	~4 GB	Lightweight fallback for limited VRAM
`gemini-2.0-flash`	Cloud	Free tier, Google quality
`qwen/qwen2.5-vl-32b-instruct:free`	Cloud	Free tier via OpenRouter
`gpt-4o`	Cloud	Best quality (paid)

🔧 Development

git clone https://github.com/Mr-JoE1/opensight-mcp.git
cd opensight-mcp
npm install
npm test                 # 21 unit tests via node:test
npm run test:watch       # Watch mode

opensight-mcp/
├── vision-mcp.mjs          # Main MCP server (8 tools)
├── vlm.mjs                 # CLI tool
├── src/
│   ├── helpers.mjs         # Pure utility functions (tested)
│   └── providers.mjs       # Multi-backend abstraction
├── tests/
│   └── helpers.test.mjs    # 21 unit tests
└── opensight-wrapper.sh    # MCP wrapper with env defaults

📄 License

MIT — see LICENSE.

Made for coding agents. Private by default. Cloud when you need it.

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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