deep-research-mcp (pminervini/deep-research-mcp) is an MCP server listed on the M8ven Trust Index. It scores 74 out of 100, grade C. It declares 3 tools. No publisher has claimed this listing.

C
Limited view
74/100

deep-research-mcp

MCP server for OpenAI's Deep Research APIs, Gemini Deep Research Agent, Allen AI's DR-Tulu, and Hugging Face's Open Deep Research

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

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Who stands behind it

pminervini

Source: Glama · also listed on github_code

Is this your MCP?

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Install from

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 4 credentials: HF_TOKEN, SERPAPI_API_KEY, SERPER_API_KEY, OPENAI_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.
🔐 secretHF_TOKENoptional, logs into Hugging Face Hub for gated models
🔐 secretSERPAPI_API_KEYor SERPER_API_KEY: enable Google-style search
🔐 secretSERPER_API_KEYSERPAPI_API_KEY or : enable Google-style search
🔐 secretOPENAI_API_KEYapi_key = "YOUR_OPENAI_API_KEY" # Defaults to
configOPENAI_BASE_URLclarification_base_url: Custom OpenAI-compatible endpoint for clarification models (optional; defaults to the main OpenAI endpoint when provider=openai, otherwise falls back to env if present)
configDEEP_RESEARCH_PROMPTS_DIR
// 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

3/3 tools missing one or more hints — deep_research (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); research_status (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); research_with_context (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.
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commit: 331d8201279ef9615577d60735801cab78932c19
code hash: 0d9181e7104ed315f9fee8c18e51b3b45b722bede9513e73d4ede6107fbd7299
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