C
Emerging
74/100
8 days ago

data-analysis-agent

Enables natural-language data analysis by loading and inspecting datasets in CSV, JSON, Excel, and Parquet formats, with session management and secure file handling.

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

Soham-Donode

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.
// 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.
configMAX_ROWS_IN_MEMORY
configMAX_FILE_SIZE_MB
configMAX_MEMORY_PER_SESSION_MB
configMAX_UNDO_DEPTH
configCHART_THUMBNAIL_KB
configUPLOAD_DIR
configOUTPUT_DIR
configLOG_LEVEL
// 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 — load_dataset (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); list_sessions (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); get_dataset_info (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.

License file

No license file

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

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/soham-donode-data-mcp-19dj5w)](https://m8ven.ai/mcp/soham-donode-data-mcp-19dj5w)
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commit: 01c5c9f068e6f50cb9e375a368fc80255d449a06
code hash: 2ed3aa053e848129765a5bc0f97e807a5c4c3b0c6a41bdb332815451b52fde79
verified: 8/14/2026, 9:50:08 AM
view raw JSON →
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