C
Emerging
74/100
9 days ago

glm-vision-mcp

Enables AI assistants to recognize and extract information from images via GLM-4V, supporting automatic screenshot recognition and MCP-based local image file reading for non-vision models like DeepSeek.

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

Code Verified⚡ Live Monitored: not connected

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⚡ Connect GitHub → continuous verification on every pushwhy connect →

Who stands behind it

lanyu-211

Source: Glama

Is this your MCP?

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// key findings
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
🔐
You'll be asked for 1 credential: ZHIPU_API_KEY
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// 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.
🔐 secretZHIPU_API_KEY## 配置 API Key () 【安全推荐】
configZHIPU_ENDPOINT
configZHIPU_MODEL
// 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

1/1 tools missing one or more hints — describe_image (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint). 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.

License file

No license file

Add a LICENSE file (MIT, Apache-2.0, etc.).

Tests exist

No test files found

Add tests that exercise each declared tool.

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 4 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/lanyu-211-glm-version-mcp-1uap0r)](https://m8ven.ai/mcp/lanyu-211-glm-version-mcp-1uap0r)
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commit: fe5f21a06dcd051253aedb2a5b22b2ea63e7d124
code hash: 0a0350cdace0e172f9a1fe9bbf23bb1907c93044a426522040df0fd4bb6d9381
verified: 8/10/2026, 8:05:24 AM
view raw JSON →
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