OpenSight MCP
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.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@OpenSight MCPanalyze 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.
๐๏ธ OpenSight 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@latestBest for | Install | |
Privacy-first, uncensored, no API keys |
| |
Zero-cost cloud vision via Google/OpenRouter | Set | |
OpenAI GPT-4o, Claude Vision, any OpenAI-compatible | Set |
Related MCP server: pic-id-mcp
๐ฏ 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 โ no code changes. | Purpose-built for MCP agents. Clipboard, file paths, URLs, base64 โ all supported. |
๐ฆ 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@latestAdd 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-mcpVerify 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 test๐ ๏ธ Tools
vision.analyze_imageโ General-purpose image analysis. Accepts data URIs (clipboard paste), base64, URLs, or file paths. Configurable system prompt, model, temperature.vision.describeโ UI/QA-focused screenshot analysis. Defaults to a QA system prompt that identifies errors, warnings, and layout issues.vision.clipboardโ Read and analyze images directly from the OS clipboard. Usesclipboardyfor cross-platform support (macOS/Windows built-in, Linux needs xclip/wl-clipboard).vision.find_imagesโ Scan common directories (~/Downloads, ~/Pictures, /tmp) for recently modified images. Zero dependencies โ pure Node.js fs.
vision.ocrโ Extract text from images using VLM or Tesseract OCR. Supports structured JSON output with text block types.vision.find_textโ Locate specific text in an image with bounding box coordinates. Supports fuzzy matching.
vision.warmupโ Pre-load the vision model into GPU VRAM to eliminate cold-start latency.vision.healthโ Check backend connection status and list available models.
๐ Backends
Configure via environment variables. The default is Ollama (local, no API keys needed).
Provider | Env Var | Free Tier | Best For |
Ollama |
| โ (your hardware) | Privacy, uncensored, offline |
Google Gemini |
| โ (Flash 2.0) | Free tier, high accuracy |
OpenRouter |
| โ (qwen-vl free) | Multi-model, free tier |
OpenAI |
| โ | 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=192.168.46.34:11434โ๏ธ Configuration
All settings via environment variables:
Variable | Default | Description |
|
| Endpoint mode: |
|
| Ollama server host (local endpoint) |
|
| Ollama API port (local endpoint) |
|
| Ollama server host (global/WAN endpoint) |
|
| Ollama API port (global/WAN endpoint) |
|
| Default vision model |
|
| Default OCR model |
|
| Backend: ollama, openai, google, openrouter |
| โ | OpenAI API key |
| โ | Google Gemini API key |
| โ | OpenRouter API key |
|
| Max response tokens |
|
| Auto-warmup model on server start |
|
| Model keep-alive duration |
|
| Request timeout (ms) |
|
| 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=11434Global (DDNS/WAN):
export VISION_ENDPOINT=global
export OLLAMA_GLOBAL_HOST=ih-tatweer.duckdns.org
export OLLAMA_GLOBAL_PORT=13313OpenCode 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"
}
}
}
}๐ 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"๐ค Recommended Models
Model | Size | Best For |
| ~5.5 GB | Default. General analysis, OCR, UI. Fast and accurate. |
| ~4 GB | Lightweight fallback for limited VRAM |
| Cloud | Free tier, Google quality |
| Cloud | Free tier via OpenRouter |
| Cloud | Best quality (paid) |
๐ง 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 modeopensight-mcp/
โโโ vision-mcp.mjs # Main MCP server (8 tools)
โโโ vlm.mjs # CLI tool
โโโ src/
โ โโโ helpers.mjs # Pure utility functions (tested)
โ โโโ providers.mjs # Multi-backend abstraction
โโโ tests/
โ โโโ helpers.test.mjs # 21 unit tests
โโโ opensight-wrapper.sh # MCP wrapper with env defaults๐ License
MIT โ see LICENSE.
Made for coding agents. Private by default. Cloud when you need it.
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