data-aggregator-mcp (musharna/data-aggregator-mcp) is an MCP server listed on the M8ven Trust Index. It scores 73 out of 100, grade C. It declares 6 tools. No publisher has claimed this listing.

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C
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73/100

data-aggregator-mcp

Unified research-data acquisition MCP — search & fetch datasets across Zenodo, DataCite, NCBI omics (GEO/SRA/BioProject), and literature (PubMed/OpenAIRE) behind one normalized model.

→ musharna/data-aggregator-mcp· listed on glama

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 Python is partially covered.

How we verified

Code Verified⚡ Live Monitored: not connected

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Who stands behind it

musharna

Source: Glama · also listed on ModelScope, github_repo_search

Is this your MCP?

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Install from

Glamanot scored hereModelScopenot scored hereGitHub

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.
✅
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 3 credentials: NCBI_API_KEY, EMBEDDING_API_KEY, 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.
configDATA_AGGREGATOR_MCP_LIVE1 LLM_API_BASE=... python scripts/eval_understand.py
configLLM_API_BASE(); with none configured the search runs unchanged and notes it in
🔐 secretNCBI_API_KEY"env": { "": "your-optional-key" }
configDATAVERSE_BASE_URL
configEMBEDDING_API_BASEembedding similarity to the query; needs , degrades to
🔐 secretEMBEDDING_API_KEYEMBEDDING_API_BASE / / EMBEDDING_MODEL — an
configEMBEDDING_MODELEMBEDDING_API_BASE / EMBEDDING_API_KEY / — an
configUNPAYWALL_EMAILenables the Unpaywall fallback leg of literature full-text
configNCBI_EMAIL
🔐 secretLLM_API_KEYLLM_API_BASE / / LLM_MODEL — an OpenAI-compatible
configLLM_MODELLLM_API_BASE / LLM_API_KEY / — an OpenAI-compatible
configDATA_AGGREGATOR_MCP_ALLOW_FILE_URLS
configCACHE_TTL_SECONDS
// quality suggestions

Tool annotations

3/6 tools have annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

6/6 tools missing one or more hints — search (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); resolve (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); fetch (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +3 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.

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/musharna/data-aggregator-mcp)](https://m8ven.ai/mcp/musharna/data-aggregator-mcp)
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commit: ea45c3f8cf25fce134713013d166d7ab5a224791
code hash: 43f9f9ad2ee752d411766b4ff1d6855f4a951fd06f84a901ff93215aee040eb7
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