three.ws Vision
NPM · @THREE-WS/VISION-MCP · SCANNED SEP 23
Image understanding for AI agents — analyze and describe any image via the three.ws pipeline.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security98
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- No install/post-install scripts declared.Pass
- 31 of 96 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency48
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 11 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability66
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 914 tokens (~304/item across 3 items; 3 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management97
- Stability observed for 29 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 3 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 4 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the three.ws Vision MCP server?
three.ws Vision runs locally as an npm package, launched with npx -y @three-ws/vision-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · @three-ws/vision-mcp
claude mcp add nirholas-vision-mcp -- npx -y @three-ws/vision-mcp
{
"mcpServers": {
"nirholas-vision-mcp": {
"command": "npx",
"args": [
"-y",
"@three-ws/vision-mcp"
]
}
}
} {
"servers": {
"nirholas-vision-mcp": {
"command": "npx",
"args": [
"-y",
"@three-ws/vision-mcp"
]
}
}
} codex mcp add nirholas-vision-mcp -- npx -y @three-ws/vision-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"nirholas-vision-mcp": {
"type": "local",
"command": [
"npx",
"-y",
"@three-ws/vision-mcp"
],
"enabled": true
}
}
} openclaw mcp add nirholas-vision-mcp --command npx --arg -y --arg @three-ws/vision-mcp
mcp_servers:
nirholas-vision-mcp:
command: "npx"
args: ["-y", "@three-ws/vision-mcp"] {
"McpServers": {
"nirholas-vision-mcp": {
"Transport": "stdio",
"Command": "npx",
"Arguments": [
"-y",
"@three-ws/vision-mcp"
]
}
}
} assistant mcp add nirholas-vision-mcp -t stdio -c npx -a -y @three-ws/vision-mcp
{
"mcpServers": {
"nirholas-vision-mcp": {
"command": "npx",
"args": [
"-y",
"@three-ws/vision-mcp"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 22 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.
- 19 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.
- 17 Sept 26 −3
- Stability: pass → 0.77 functional
- 16 Sept 26 +1
- Stability: 0.97 → pass security
- 14 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.
- 11 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.
- 10 Sept 26 −3
- Stability: pass → 0.80 functional
- 9 Sept 26 +1
- Stability: 0.97 → pass security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 23 Sept 2026 · Analysed npm/@three-ws/vision-mcp@0.1.1
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Dependencies 96 packages
| Packages resolved | 96 |
|---|---|
| Stale | 31 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
analyze_image Analyze an image against a prompt ~321
Let the agent SEE an image and answer a question about it. Supply the image as `imageUrl` (a public https URL the vision server fetches) OR `image` (raw base64 / a data: URI), and a `prompt` describing what to extract — e.g. "What objects are in this scene?", "Read the text in this screenshot", "Is this avatar render rigged correctly?". Returns the model's answer as `text`, plus the `provider` and `model` that served it (a free NVIDIA NIM lane when available, an automatic paid backstop otherwise — the caller never pays). Analysis only: it does not store or mutate anything. Accepts JPEG, PNG, WebP, or GIF up to 12 MB; base64 inputs are size-checked before upload.
| Name | Type | Req | Description |
|---|---|---|---|
| image | string | – | The image as raw base64 or a `data:image/...;base64,...` URI. Provide this OR `imageUrl`, not both. |
| imageType | string | – | MIME type of a raw base64 `image` (ignored for data URIs / `imageUrl`). Defaults to image/jpeg. |
| imageUrl | string | – | Public https URL of the image to analyze. Provide this OR `image`, not both. |
| maxTokens | integer | – | Maximum tokens in the answer (16–2048). Higher = longer, more detailed reads. Default 512. |
| prompt | string | yes | The question or instruction about the image (what to extract, read, classify, or critique). |
No output schema declared.
No examples provided.
describe_image Describe an image in natural language ~313
Get a plain-language description of an image — ideal for alt text, captions, or a quick "what is this?" read when you have no specific question. Supply the image as `imageUrl` (a public https URL) OR `image` (raw base64 / data: URI). Use `detail` to pick brief / standard / detailed, and `focus` to steer the description toward something specific (e.g. "the clothing", "any visible text"). Returns the prose as `description`, plus the `provider` and `model` that served it (free NVIDIA NIM first, automatic paid backstop otherwise — the caller never pays). Read-only; accepts JPEG, PNG, WebP, or GIF up to 12 MB.
| Name | Type | Req | Description |
|---|---|---|---|
| detail | string | – | How much description to return: brief (one sentence), standard (2–3 sentences), or detailed (a full paragraph). |
| focus | string | – | Optional aspect to emphasize in the description (e.g. "any visible text", "the background", "the pose"). |
| image | string | – | The image as raw base64 or a `data:image/...;base64,...` URI. Provide this OR `imageUrl`, not both. |
| imageType | string | – | MIME type of a raw base64 `image` (ignored for data URIs / `imageUrl`). Defaults to image/jpeg. |
| imageUrl | string | – | Public https URL of the image to describe. Provide this OR `image`, not both. |
No output schema declared.
No examples provided.
get_vision_status Vision availability + accepted formats ~106
Check whether the three.ws vision pipeline is live on the target deployment and which image formats it accepts. Returns `configured` (true when at least one VLM provider — a free NVIDIA NIM lane or the paid backstop — can serve a request) and `image_types` (the accepted MIME types). Use this before calling analyze_image / describe_image so the agent can decide whether to offer a "describe this image" action. No image, no key, no cost.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
What is the three.ws Vision MCP server?
three.ws Vision is an MCP server listed in the public MCP registry as io.github.nirholas/vision-mcp. Image understanding for AI agents, analyze and describe any image via the three.ws pipeline. This page covers its npm package (@three-ws/vision-mcp).
Is the three.ws Vision MCP server safe to use?
three.ws Vision scores 82 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 23 September 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the three.ws Vision MCP server expose?
three.ws Vision exposes 3 tools: analyze_image, describe_image, get_vision_status. Their descriptions and schemas cost roughly 740 tokens of context every time the server is loaded.
Is the three.ws Vision MCP server still maintained?
three.ws Vision is still listed as active in the MCP registry. We last reached this channel on 23 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the three.ws Vision MCP server under?
three.ws Vision declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.