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    Enables deep research into cryptocurrency tokens by gathering data from multiple sources like CoinGecko and DeFiLlama to generate structured reports. It allows users to track research progress, fetch web content, and manage resources locally for comprehensive crypto analysis.
    9
    68 npm
    4
    Apache 2.0
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    MCP server that automates audit risk assessment from Korean DART disclosures, providing deterministic risk signals, going-concern scoring, and memo draft generation without LLM judgment.
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    Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.
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    Apache 2.0
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    Reads PDF, image, or video files by sniffing format and delegating to specialized sibling MCP servers, extracting facts and metadata without LLMs.
    29 npm
    MIT
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    MCP server for searching and reading arXiv papers from AI assistants, with built-in rate limiting to avoid API blocks.
    1
    MIT
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    Provides tools to research crypto trading strategies via backtesting, walk-forward validation, and paper trading, with a deflated-Sharpe overfitting check. Enables natural-language-driven analysis and interpretation of strategy performance.
    3
    Apache 2.0
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    MCP server for querying hydroponic sensor data stored in PostgreSQL/TimescaleDB. Provides tools to list tables, describe schemas, read recent sensor readings, fetch latest data, and perform time-series aggregations via natural language.
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    An AI Concierge replaces static forms with adaptive AI conversations that understand real situations, structure key information automatically, and trigger the right next step. Rigid forms cause drop-off, weaken qualification, and strip away context. Perspective uses adaptive AI to capture structured data and trigger automation, so you understand what truly matters to your customers and can make d
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    MIT
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    Enables real-time tracking of AI/LLM research progress by searching and aggregating content from arXiv, GitHub, Hugging Face, and Papers with Code. Supports intelligent search, automated daily/weekly research summaries, and covers 15+ AI research areas with smart caching.
    8
    MIT
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    MCP server for semantic research: search arXiv, fetch papers, and answer questions grounded in the actual paper text via RAG tools, resources, and prompts.
    1
    MIT
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    Enables AI-native statistical analysis and reproducible research workflows through MCP, including natural language planning, protocol-based analysis, Python/R cross-validation, and publication-ready figure generation.
    MIT
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    Integrates with Orca AI's HUNT Platform API to search for information about people, companies, and entities, enabling AI assistants to access investigative intelligence and due diligence data.
    MIT