"Information on Conducting In-Depth Research Techniques" matching MCP servers:

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

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.

Orchestrates distributed research drones on Google Cloud Run, enabling scalable and bidirectional research task management.

Persistent memory and pattern learning for AI coding assistants via MCP.

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.

An MCP server for academic literature research that integrates Scopus, CrossRef, OpenAlex, and Unpaywall to search documents, get abstracts, author profiles, citing papers, and open-access PDF links.

A Python-based agent that integrates research providers (OpenAI, Gemini, DR-Tulu, Open Deep Research) with Claude Code via the Model Context Protocol for automated deep research.

Enables AI agents to search videos, retrieve metadata and transcripts, pinpoint exact moments via hybrid semantic search, and conduct multi-video research with timestamp deep links—all without YouTube API keys.

A deep-research MCP server exposing a single task-augmented tool that runs GPT-Researcher with Tavily search, Anthropic Claude, and OpenAI embeddings, streaming progress via MCP tasks and Upjack entity stream.

Enables YouTube integration with Claude Code, including video search, metadata retrieval, transcript fetching, channel exploration, and trending videos.

Enables declarative FDTD validation, guarded cloud-task workflows, and normalization of Tidy3D simulation results into metadata and bounded CSV observables, while keeping credentials and cloud-execution privileges isolated.

MCP server that searches 9 sources, scrapes full content, reranks results, and synthesizes cited answers with free LLMs.

An MCP server for cross-platform social media research that enables scraping, semantic search, and analysis across seven major social platforms. It uses Apify for data retrieval and stores results in a local database for AI-powered trend detection and profile analysis.

MCP server that integrates a 1200-paper RAG database with six tools to support research workflows across stages like hypothesis, experiment, statistics, and writing. It routes requests to specialized skills and real-time frontier searches to provide evidence-grounded research mentoring.

Searches open-access research papers by keyword and retrieves detailed metadata by CORE ID, including titles, authors, abstracts, DOIs, and download links.

Enables querying a single academic paper by DOI, PMID, or arXiv ID to retrieve its open-access copies, licenses, linked datasets, code, citations, and retraction status from multiple scholarly sources in one call.

MCP server that answers questions using Reddit discussions as evidence, searching threads, fetching comments, and ranking useful context, with optional cited answer synthesis.

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.

Exposes fourteen read-only tools over the HEY Research public API, letting assistants look up Robinhood Chain projects, builders, shipped work, relationships and market context, with each answer tagged FACT, DERIVED or UNKNOWN and unmeasured fields omitted rather than zeroed. Runs over stdio or hosted Streamable HTTP, and gives no trade instructions.

Aggregates multiple MCP services into a single unified interface with self-configuration capabilities, enabling dynamic addition and removal of tools via conversation.