VELMA (Yunsmn/VELMA) is an MCP server listed on the M8ven Trust Index. It scores 74 out of 100, grade C. It declares 15 tools. No publisher has claimed this listing.

Back to MCP Trust IndexM8ven
C
Emerging
74/100
9 days ago

VELMA

MCP server for controlling a simulated robot arm with vision-based pick-and-place, driven by LLM or manual control.

→ Yunsmn/VELMA· 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

Yunsmn

Source: Glama

Is this your MCP?

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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.
🔐
You'll be asked for 1 credential: LLM_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.
configSO101_EXPOSE_TRUTHserver with =1 — never set this when an LLM is connected).
configSO101_SCENEmodels/so101/<scene>.xml overrides the scene (default pick_and_place_scene.xml).
configSO101_VIEWERSet =1 to watch the arm instead — but perception is then disabled by design (the
configSO101_PORT
configMCP_URL
configLLM_BASE_URLhelp for endpoint/model flags (, LLM_API_KEY, --mode autonativetext).
🔐 secretLLM_API_KEYhelp for endpoint/model flags (LLM_BASE_URL, , --mode autonativetext).
configLLM_MODEL
configLLM_TIMEOUT
configMCP_READ_TIMEOUT
// 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

15/15 tools missing one or more hints — get_initial_instructions (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); get_robot_state (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); move_to_position (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +12 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.

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/yunsmn/velma)](https://m8ven.ai/mcp/yunsmn/velma)
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commit: 34f72d0fb80b5cf1dc66eed6b7632d26c1ad7f77
code hash: c2f50e61d70553cd9c177169e3ab2badc554a1570b12e2c676e2349859324dfe
verified: 9/3/2026, 2:31:33 PM
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