"Data science and deep learning papers" matching MCP servers:

Provides 102 tools for end-to-end data science pipelines, enabling data loading, cleaning, visualization, modeling, and reporting via natural language.

Enables time-series analysis and forecasting through a structured tool catalogue, including data loading, quality repair, diagnostics, and forecasting with ARIMA, exponential smoothing, Chronos-2, Toto 2.0, and AutoML.

Data Science AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

MCP server for scientific grounding: search and discover open-access research papers across arXiv, OpenAlex, Crossref, PubMed, and Semantic Scholar, and retrieve references/citations from paywalled journals via public DOI/abstract metadata.

Enables local MCP clients to search software names, look up exact identifiers, and retrieve project summaries, packages, and direct dependencies from ecosyste.ms Science, with an optional offline SQLite snapshot for lookup.

MCP server for AI-assisted research: paper ingestion, semantic search, citation graph traversal, cross-domain knowledge synthesis, and workflow automation.

Monitors PubMed and medRxiv for configurable research topics, summarizes papers using a local LLM, and stores deduplicated results in a local database.

An MCP server that enforces a pedagogical workflow to teach topics step by step, using research, decomposition, and spaced retrieval practice.

Enables LLMs to search and retrieve academic papers from arXiv by topic, author, category, or ID.

Enables semantic search across scientific papers in your Zotero library with hybrid search, incremental indexing, and cross-encoder reranking.

Enables developers to record feature-based development processes and turn Git changes, AI conversations, token usage, technical decisions, and debugging attempts into structured Obsidian learning reviews.

A read-only MCP server for searching control science and engineering papers via OpenAlex, limited to core journals in the field.

Unified academic paper search MCP server integrating OpenAlex, Semantic Scholar, CrossRef, and arXiv APIs, enabling Claude to search and analyze over 500 million scholarly papers.

Enables fully local, end-to-end research automation: reproducing papers from PDF into runnable code and verified artifacts, writing papers section-by-section with LaTeX/PDF/DOCX export, and running an ideate→debate→design→verdict research pipeline—all without an API key.

Enables deep research tasks using a multi-agent architecture that integrates any LLM and MCP tools. Available via MCP stdio, streamable HTTP, and SSE transports.

AI learning assistant for families. Manages game time rewards based on school grades, homework, and bonus tasks. Syncs with EduPage/PRONOTE. 78 MCP tools with instruction workflows.

Enables the AI Learning Assistant to perform web searches for current or external information, returning ranked public-web results with titles, URLs, snippets, and scores over Streamable HTTP.

Provides MCP-compatible tools for data analysis, including file reading, Python/SQL execution, and hypothesis testing. Enables autonomous data analysis agents to interact with a sandboxed environment.

Turns your PDFs into locally stored flashcards and quizzes, grades your answers, and schedules spaced-repetition reviews entirely on your machine.

An open-source deep research MCP server that provides multi-source web search and synthesis with citations, enabling agents to perform citation-backed research using Qwen3-30B-A3B-Thinking and other models.