videre-mcp (Veedubin/Videre-MCP) is an MCP server listed on the M8ven Trust Index. It scores 74 out of 100, grade C. It declares 6 tools. No publisher has claimed this listing.

Back to MCP Trust IndexM8ven
C
Emerging
74/100

videre-mcp

Bridges vision models to text-only coding models using Florence-2, enabling non-vision LLMs to describe images, extract text, and analyze screenshots via MCP tools.

→ Veedubin/Videre-MCP· listed on glama

Emerging. No concerning findings. Grades remain capped until the project builds reputation through adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

How we verified

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Who stands behind it

Veedubin

Source: Glama

Is this your MCP?

Claim it to get a verified publisher badge, a free copy of our full audit findings, and direct contact for any high-priority issues we find. Or connect your repo for our deepest verification, Live Monitored: read-only, revoke anytime. What we access →

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Install from

Glamanot scored here

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

// key findings
✅
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
✅
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
// tools this server exposes10 tools · 4 behind config

These names and descriptions are the publisher's own, read from the source code. We print them as written. Our assessment is the findings above, not this list.

describe_image

Describe an image in natural language using Florence-2.

ocr_image

Extract text from an image using Florence-2 OCR.

describe_screenshot

Describe UI regions in a screenshot using Florence-2.

take_screenshot

Capture a screenshot and optionally describe it using Florence-2.

ocr_paddle

Extract text from an image using PaddleOCR (100+ languages, production-grade).

parse_document

Parse a document (PDF, DOCX, PPTX, HTML, MD) into structured output using Docling.

save_image_memorybehind config

Save an image to vision memory with associated text and CLIP embedding.

query_imagesbehind config

Query stored images by text using cross-modal CLIP search.

list_imagesbehind config

List stored images chronologically — the progression/timeline view.

get_imagebehind config

Retrieve image metadata by image_id or memory_id.

// environment variables
To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.
configMEMINI_MODEL_NAME
// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

10/10 tools missing one or more hints — describe_image (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); ocr_image (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); describe_screenshot (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +7 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 2 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/veedubin/videre-mcp)](https://m8ven.ai/mcp/veedubin/videre-mcp)
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commit: 9dcdbb8fe62edb3550982f4c52685ee06c43e822
code hash: 870dd2e959a3db94d21c2e3ae187efcfe02cde1383ada0bd0251890277161ad4
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