THU Agent by CyberCraze (cybercrazetech/THU-deepseek-glm-api-mcp-server) is an MCP server listed on the M8ven Trust Index. M8ven has not graded it: we have no way to read this server ourselves. No publisher has claimed this listing.

C
Limited view
69/100
2 months ago

THU Agent by CyberCraze

An interactive coding agent and MCP server that provides access to various AI models via the Tsinghua University lab proxy API. It enables users to inspect files and execute shell commands within their local directory using models like DeepSeek, GLM, and Qwen.

Limited view. Automated analysis covers part of this stack. Findings reflect what we verified. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

Limited view: static analysis for HTML is partially covered.

How we verified

Code Verified⚡ Live Monitored: not connected

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Who stands behind it

cybercrazetech

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 3 credentials: THU_LAB_PROXY_API_KEY, TSINGHUA_DEEPSEEK_API_KEY, DEEPSEEK_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.
configTHU_AGENT_FOLD_WIDTH
configTHU_AGENT_MULTIMODALImage files can be sent as multimodal content only when the selected model/proxy supports it and =1 is set. Otherwise they are treated as file references.
configTHU_AGENT_MODEL
configTHU_LAB_PROXY_MODEL
configTHU_LAB_PROXY_BASE_URLexport ='https://lab.cs.tsinghua.edu.cn/ai-platform/api/v1'
🔐 secretTHU_LAB_PROXY_API_KEYexport ='your_proxy_key_here'
🔐 secretTSINGHUA_DEEPSEEK_API_KEY
🔐 secretDEEPSEEK_API_KEY
configTSINGHUA_DEEPSEEK_BASE_URL
configTSINGHUA_DEEPSEEK_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

4/4 tools missing one or more hints — list_models (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); health_check (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); simple_chat (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +1 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.

Tool inputs are validated

3/4 tool handlers declare input schemas (75%)

Declare an inputSchema with zod/joi/yup on every tool definition.

Tool handlers catch errors

Only 0/4 tool handlers wrap calls in try/catch (0%)

Wrap each tool handler body in try/catch and return a structured error response.

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 6 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/cybercrazetech-thu-deepseek-glm-api-mcp-server-1kt5cn)](https://m8ven.ai/mcp/cybercrazetech-thu-deepseek-glm-api-mcp-server-1kt5cn)
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commit: 54e7aaf044b08e2ed277dc6c6656c72c0c453450
code hash: c37bec6d39a8e43bfec71177299934133f256031272e1ee38eda4992a2ac34a4
verified: 6/16/2026, 12:03:29 PM
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