MCP Deep Research Server using Gemini creating a Research AI Agent

Academic Research Skills for Claude Code: research → write → review → revise → finalize

Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.

An autonomous agent that conducts deep research on any data using any LLM providers

Anti-hallucination research mode for Claude Code. Toggle on/off to enforce citation requirements and source grounding.

900+ pure-markdown skills for autonomous AI research, organized as 9 freely-composable packages over a 4-layer hierarchy (Campaign → Strategy → Tactic → SOP). Non-linear orchestration with backtracking, 6 MCP integrations. The AI is the researcher — you set the direction.

The automated approach leverages the cross-combination of high-quality papers from top conferences to uncover feasible research and innovation ideas. Through multi-level verification and convergence screening, it identifies research schemes that are feasible and have in-depth value.

42 AI agent skills for literature review, academic writing, citation verification, conference submission, rebuttal, publication, and presentations.

Open-source Agent Skills for planning, drafting, revising, and polishing SCI/SSCI papers—while preserving evidence, citations, and claim strength.

Agent-driven research knowledge base. Agents collect, search, and synthesize web research into a persistent, searchable wiki.

Open source implementation and extension of Google Research’s PaperBanana for automated academic figures, diagrams, and research visuals, expanded to new domains like slide generation.

Claude Code plugin for autonomous AI research — multi-agent loops take a bare topic all the way to running experiments, with no human-written experimental code.

A curated list of research-oriented skills usable in OpenAI Codex, covering writing, literature review, evaluation, and research workflows.

MCP server for enabling LLM applications to perform deep research via the MCP protocol

NotebookLM does the research, Claude writes the content. Research → Synthesis → Content Creation → Publishing. Claude Code Skill + MCP Server.

Claude Code Plugin for Self-maintaining research knowledge graph for Claude Code + Obsidian

Deepdive skill for Claude Code — 12-phase research pipeline: plan-review gate, parallel sub-agent search, claims-ledger triangulation with dissent protection, relevance × authority evidence filter, multi-angle red team, four-layer citation verification. 105 blocks, 29 channels, 460+ stat sources, 47 APIs, 1072 verified endpoints.

Agent Skills for medical research — literature search, reporting-guideline & citation checks, statistics, publication figures, submission. Works with Claude Code, Codex, Cursor & GitHub Copilot. Built by a physician-researcher, tested on real publications. MIT.

13 curated Agent Skills for research, product decisions, decks, publishing, audits, and more — portable across skills-compatible agents.

239 evaluated academic Claude/agent skills across 17 research domains (bioinformatics, data science, clinical, social-science methods, Turkish academia & more). Executable eval per skill, deterministic citation verifier, research→write→review→publish pipeline, and a skill-finder front door. Claude Code, Cursor, Codex, Gemini CLI & Copilot.

Composable computational-science methodology skills for AI research agents — pre-registration over TDD. A science-domain reimplementation of Superpowers.

Academia MCP server: Tools for automatic scientific research

CoexistAI is a modular, developer-friendly research assistant framework . It enables you to build, search, summarize, and automate research workflows using LLMs, web search, Reddit, YouTube, and mapping tools—all with simple MCP tool calls or API calls or Python functions.

A curated, multilingual library of 182 installable AI agent skills for end-to-end academic research—spanning literature discovery, scientific writing, grant development, bioinformatics, drug discovery, clinical research, machine learning, and data analysis.