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An autonomous MCP agent designed for deep web and local research, providing detailed, factual, and unbiased reports with citations for any given task.

A comprehensive open-source library of skills that empowers AI agents to autonomously conduct AI research, from ideation and experimentation to paper writing.

This MCP server allows AI agents to generate in-depth research reports rapidly, supporting various LLMs and web search engines with local data processing.

hyperresearch

jordan-gibbs

This plugin transforms Claude Code or OpenAI Codex into a powerful deep research agent that collects, synthesizes, and stores web research into a persistent, searchable knowledge base.

This MCP server allows AI agents to read arXiv papers, extract BibTeX, and keep topic watches, with papers stored locally.

This skill provides a structured, human-in-the-loop research workflow for AI agents to generate outlines and conduct deep investigations on various topics.

Engram is an evidence-based learning plugin that turns AI agents into tutors to help humans learn and retain information.

This autonomous AI research engine conducts computational experiments, generates code, executes training, and produces full LaTeX papers with real experimental data.

This MCP server and Zotero plugin allow your AI assistants like Claude to deeply integrate with Zotero, enabling smart search, content extraction, and semantic analysis of your literature library.

This plugin provides guardrails and skills for Claude Code to perform academic research tasks like paper reproduction, experiment design, and review, preventing common AI mistakes.

Audits autoresearch papers for self-consistency and fabrication using 61 integrity signals, providing a deterministic verdict.

This implements a Parallel-Agent Reinforcement Learning (PARL) paradigm for training AI models to decompose tasks into parallel subtasks and coordinate multiple agents.

A Claude Skill that organizes course materials, PDFs, and PPTs into Markdown/Obsidian revision notes.