Glm-Vision-Mcp (cfj3191449485-pixel/Glm-Vision-Mcp) is an MCP server listed on the M8ven Trust Index. M8ven has not graded it: there is no public source to read and no endpoint we can reach, so there is nothing for us to inspect. No publisher has claimed this listing.

Back to MCP Trust Indexm8ven
C
Emerging
74/100
9 days ago

Glm-Vision-Mcp

A local MCP server that adds image recognition to text-only LLMs by sending images to Zhipu's free vision models, supporting local files, URLs, and base64 inputs with automatic model fallback.

→ cfj3191449485-pixel/Glm-Vision-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

Code Verified⚡ Live Monitored: not connected

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Who stands behind it

cfj3191449485-pixel

Source: Glama

Is this your MCP?

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Install from

Glama

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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.
✅
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
🔐
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用记事本 / VS Code 等文本编辑器打开项目根目录里的 .env 文件，把那一行里等号后面的内容换成你自己的 key（保留 = 这几个字，只换后面的值）：
configZHIPU_VISION_MODELS"": "glm-4.6v-flash,glm-4.1v-thinking-flash,glm-4v-flash"
configZHIPU_VISION_MODEL（可选，兼容） 若只填此项，则只用该单一模型、不降级
configZHIPU_API_BASE当前实现对接智谱 OpenAI 兼容接口（open.bigmodel.cn）。若要接千问 Qwen-VL 等，改 和模型名通常即可，兼容 OpenAI chat/completions 格式的供应商基本可直接复用。
// 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.

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 3 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/cfj3191449485-pixel-glm-vision-mcp-1krjj7)](https://m8ven.ai/mcp/cfj3191449485-pixel-glm-vision-mcp-1krjj7)
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commit: fa4d6815a8ac1a70ecca7ef222657ae37fb9b2b1
code hash: fe21c23b36f29301be33e659cf104fe21c4356cdc774e19a9017193f0eb94e4b
verified: 8/17/2026, 7:36:29 PM
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