sentimatix 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.

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sentimatix

# Sentimatix: Indian Stock Market Intelligence Sentimatix is a high-fidelity financial intelligence API and MCP server designed specifically for the **National Stock Exchange of India (NSE)**. It provides AI agents, algorithmic traders, and quantitative developers with deep, structured insights into over 2,200 Indian equities. ## What it does By combining real-time financial news ingestion with advanced NLP sentiment analysis and historical market data, Sentimatix acts as an automated quantita

· 2K installs· listed on smithery

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sentimatix

Source: Smithery

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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.

// quality suggestions

All four hints declared on every tool

10/10 tools missing one or more hints — explain_price_change (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); analyze_stock_enhanced (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); compare_stocks (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +7 more. OpenAI's directory rejects tools where any hint is 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.

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// 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 1 concrete improvement we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
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code hash: b6cf769f069bfaffcf00380ef58332fe1a77dd959c62bcb4af798fb775d86c05
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