Vision Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Vision Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
MCP server that exposes an analyze_image tool backed by an OpenAI-compatible vision LLM (GPT-4o, Qwen-VL, etc.).
Provides a single MCP tool analyze_image that accepts an image via:
data: prefix)and returns a text description from the configured vision model.
fetch required)Set these environment variables when configuring the MCP server:
| Variable | Required | Default | Description |
|---|---|---|---|
VISION_BASE_URL | No | https://api.openai.com/v1 | OpenAI-compatible API base URL |
VISION_API_KEY | Yes | — | API key for the gateway |
VISION_MODEL | No | gpt-4o | Vision model name |
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>"
}
}
}
}{
"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>"
}
}
}
}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>" }[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>" }analyze_image| Parameter | Type | Required | Description |
|---|---|---|---|
path | string | one of three | Local file path to the image |
url | string | one of three | Public http(s) URL of the image |
base64 | string | one of three | Raw base64 string |
mime_type | string | No | Override MIME type (auto-detected) |
prompt | string | No | What to ask the model (defaults to detailed description) |
model | string | No | Override model per call |
max_tokens | integer | No | Default 4096 |
temperature | number | No | Default 0.2 |
detail | string | No | low / high / auto |
system | string | No | Optional system message |
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 smokeMIT
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.