"Research assistant for AI and ML papers, code, and methodology" matching MCP servers:

Enables discovery, retrieval, summarization, comparison, methodology and limitation analysis, research gap identification, and local management of academic papers via arXiv and Gemini AI.

Provides machine learning researchers with tools for creating publication-quality scientific visualizations, statistical plots, and 2D data representations. It streamlines the research workflow by enabling AI assistants to generate complex figures from CSV, JSON, or direct data inputs.

An MCP server that provides tools, resources, and prompts for reading, writing, and summarizing research notes stored in a local flat-file database.

An offline MCP server that enables research tasks such as summarizing text, extracting key points, and saving/retrieving notes via a CLI client and stdio transport.

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

A custom MCP server that enables AI assistants to perform comprehensive research tasks, including searching ArXiv, summarizing papers via Groq, managing local research notes, and pushing findings to GitHub.

An MCP server that enables saving, retrieving, and managing research content using ChromaDB vector storage and semantic search.

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.

A research assistant server that enables saving, organizing, and retrieving research content with semantic search using ChromaDB and OpenAI embeddings.

Enables searching for upcoming academic conferences and events from WikiCFP by keywords, returning detailed information including dates, locations, submission deadlines, and related resources.

A stock research MCP server that enables natural-language queries for market data, watchlist management, company analysis, and research note tracking, using FastMCP and Databricks Lakebase Postgres.

Enables searching and retrieving molecular hydrogen medical literature from H2 Papers database, with per-paper safety notes always included in results.

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.

Enables host assistants to discover and read the toolkit’s research methods over a local stdio MCP connection, supporting research planning, literature work, scientific reasoning, writing, figures, and academic document workflows. It does not itself search scholarly databases, generate research results, compile documents, or call models.

Enables AI to save, organize, search, and synthesize research materials using a local vector database with support for both OpenAI and Ollama backends.

Enables agents to search, analyze, and explore arXiv academic papers with advanced multi-field search, author lookup, category browsing, citation extraction, and bibliography export.

Enables researchers to search ArXiv papers, extract key insights (problems, methods, results) from abstracts, and perform ML-powered analysis including topic modeling, trend visualization, and author collaboration networks.

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

Enables searching and reading of AI/ML papers from conference proceedings and arxiv, with tools for full-text search, table of contents, and content grep.

Enables assistants to search, fetch daily curated lists, retrieve metadata, and generate citations for Hugging Face papers.

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

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 natural-language evaluation, explanation, and reporting of any trained ML model, including performance metrics, prediction insights, drift detection, and PDF report generation.

Papers by Ouroboros Apps (https://ouroborosapps.com). Research paper search with real citations from OpenAlex, Semantic Scholar, PubMed, Crossref, and arXiv: find papers, fetch abstracts, follow citations, and format references. Connect by pasting https://papers-mcp.vercel.app/mcp into Claude, Cursor, Grok, or ChatGPT developer mode (OAuth). Docs: https://ouroborosapps.com/docs/papers

An MCP server that gives AI agents the ability to profile a CSV, define an ML task, tune XGBoost and LightGBM with Optuna, and produce a markdown report with feature importance, all from natural language.

Enables autonomous auditing of scientific papers for methodology flaws, identifying selection bias and p-hacking, while computing consensus ratios and verifying citation credibility through MCP-compliant tooling.

Enables auditing scientific papers for methodological biases such as selection bias and p-hacking, and assessing citation credibility and research consensus.

Enables AI assistants to query ClinicalTrials.gov and PubMed for research evidence, and to compare regulatory document changes against internal files, with strict read-only access and no ability to modify or export data.

A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.

Enables comprehensive academic research by searching and analyzing papers from PubMed, Google Scholar, ArXiv, and JSTOR. Provides full-text access, citation management, and research organization through five powerful consolidated tools.