vision-mcp
Integrates with OpenAI-compatible vision models to analyze images, providing image descriptions or answering prompts about image content.
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., "@vision-mcpdescribe the image at https://example.com/cat.jpg"
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.
@winton979/vision-mcp
MCP server that exposes an analyze_image tool backed by an OpenAI-compatible vision LLM (GPT-4o, Qwen-VL, etc.).
What it does
Provides a single MCP tool analyze_image that accepts an image via:
path — local file path
url — public http(s) URL
base64 — raw base64 string (with or without
data:prefix)
and returns a text description from the configured vision model.
Related MCP server: read-image-mcp
Prerequisites
Node.js ≥ 18 (global
fetchrequired)
Configuration
Set these environment variables when configuring the MCP server:
Variable | Required | Default | Description |
| No |
| OpenAI-compatible API base URL |
| Yes | — | API key for the gateway |
| No |
| Vision model name |
Claude Code setup
macOS / Linux
Add to ~/.claude.json or ~/.claude/.mcp.json:
{
"mcpServers": {
"vision": {
"command": "npx",
"args": ["-y", "@winton979/vision-mcp"],
"env": {
"VISION_BASE_URL": "<your-base-url>",
"VISION_API_KEY": "<your-api-key>",
"VISION_MODEL": "<your-model>"
}
}
}
}Windows
{
"mcpServers": {
"vision": {
"command": "cmd",
"args": ["/c", "npx", "-y", "@winton979/vision-mcp"],
"env": {
"VISION_BASE_URL": "<your-base-url>",
"VISION_API_KEY": "<your-api-key>",
"VISION_MODEL": "<your-model>"
}
}
}
}Codex setup
macOS / Linux
Add to ~/.codex/config.toml:
[mcp_servers.vision-mcp]
type = "stdio"
command = "npx"
args = ["-y", "@winton979/vision-mcp"]
env = { VISION_BASE_URL = "<your-base-url>", VISION_API_KEY = "<your-api-key>", VISION_MODEL = "<your-model>" }Windows
[mcp_servers.vision-mcp]
type = "stdio"
command = "npx"
args = ["-y", "@winton979/vision-mcp"]
env = { VISION_BASE_URL = "<your-base-url>", VISION_API_KEY = "<your-api-key>", VISION_MODEL = "<your-model>" }Tool: analyze_image
Parameter | Type | Required | Description |
| string | one of three | Local file path to the image |
| string | one of three | Public http(s) URL of the image |
| string | one of three | Raw base64 string |
| string | No | Override MIME type (auto-detected) |
| string | No | What to ask the model (defaults to detailed description) |
| string | No | Override model per call |
| integer | No | Default 4096 |
| number | No | Default 0.2 |
| string | No |
|
| string | No | Optional system message |
Local development
git clone https://github.com/winton979/vision-mcp.git
cd vision-mcp
npm install
npm run build
# Run smoke test
SMOKE_IMAGE=/path/to/test.png VISION_API_KEY=sk-... npm run smokeLicense
MIT
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