Image Label
PYPI · LABEL-IMAGE-MCP
Manage images and annotations in the Image Label app, and export COCO or YOLO datasets.
Available components
Last scanned (5 hours ago)
Scores higher than 62% of PyPI servers
Category AI and Machine Learning
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 Security50
- Malware scan not yet available for this package.Unverified
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 0 of 29 dependencies flagged as unhealthy. View diagnostics → Pass
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to sachinbkale27/label-image-mcp). View diagnostics → Pass
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 0 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability57
- AI-judged instruction clarity (fair).Partial
- Tool/resource definitions use about 341 tokens (~42/item across 8 items; 8 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
- Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "remove_annotations" implies "remove" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 8 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
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
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.
- 17 Oct 26 59
First indexed and scored.
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 18 Oct 2026 · Analysed pypi/label-image-mcp@0.1.0
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | sachinbkale27/label-image-mcp |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/sachinbkale27/label-image-mcp/.github/workflows/release.yml@refs/tags/v0.1.0 |
| Rekor log index | 3290684954 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:5af9d3cd970133a99e3d6cf9b3f5fe61c6714a91483bbfc960b13aed7a464eb8 |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 29 packages
| Packages resolved | 29 |
|---|---|
| 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 →
add_annotations ~34
Append annotations to an image, keeping the existing ones.
| Name | Type | Req | Description |
|---|---|---|---|
| annotations | array | yes | – |
| image_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
export_annotations ~47
Export an image's polygon and circle annotations as COCO JSON or YOLO, same as the web app's export.
| Name | Type | Req | Description |
|---|---|---|---|
| format | string | – | – |
| image_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_image ~36
Get one image's metadata, all annotations, and a signed viewing URL (valid 24h).
| Name | Type | Req | Description |
|---|---|---|---|
| image_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
list_images ~42
List images saved in Image Label, optionally filtered by category (case-insensitive). Returns summaries; use get_image for annotations and the viewing URL.
| Name | Type | Req | Description |
|---|---|---|---|
| category | – | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | array | yes | – |
No examples provided.
remove_annotations ~34
Remove specific annotations from an image by their ids.
| Name | Type | Req | Description |
|---|---|---|---|
| annotation_ids | array | yes | – |
| image_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
replace_annotations ~42
Replace ALL annotations on an image with the given list. Pass an empty list to clear them.
| Name | Type | Req | Description |
|---|---|---|---|
| annotations | array | yes | – |
| image_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
update_image_metadata ~58
Update an image's name, category, sub-category or description. Omitted fields are left unchanged.
| Name | Type | Req | Description |
|---|---|---|---|
| category | – | – | – |
| description | – | – | – |
| image_id | string | yes | – |
| name | – | – | – |
| sub_category | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
upload_image ~48
Upload a local image file (path on the machine running this server) to Image Label.
| Name | Type | Req | Description |
|---|---|---|---|
| category | – | – | – |
| description | – | – | – |
| name | – | – | – |
| path | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
How do I install the Image Label MCP server?
Image Label runs locally as a PyPI package, launched with uvx label-image-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · label-image-mcp
claude mcp add sachinbkale27-label-image-mcp -- uvx label-image-mcp
What is the Image Label MCP server?
Image Label is an MCP server listed in the public MCP registry as io.github.sachinbkale27/label-image-mcp. Manage images and annotations in the Image Label app, and export COCO or YOLO datasets. This page covers its PyPI package (label-image-mcp).
Is the Image Label MCP server safe to use?
Image Label scores 59 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 18 October 2026. Its build provenance is signed and verified. 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 Image Label MCP server expose?
Image Label exposes 8 tools: list_images, get_image, update_image_metadata, add_annotations, replace_annotations, and 3 more. Their descriptions and schemas cost roughly 341 tokens of context every time the server is loaded.
Is the Image Label MCP server still maintained?
Image Label is still listed as active in the MCP registry. We last reached this channel on 18 October 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 Image Label MCP server under?
Image Label declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.