"Information on conducting deep research" matching MCP servers:

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.

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.

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.

Provides specialized AI-powered comprehensive research and analysis capabilities by integrating with advanced deep research agents, offering unlimited queries with no rate limits and faster performance than comparable services.

An agent-based tool that provides web search and advanced research capabilities including document analysis, image description, and YouTube transcript retrieval.

Web search, clean page reading & one-call research dossiers for AI agents. No API key — your agent does the synthesis.

Enables configuration-driven, budgeted multi-source web research across platform and web search adapters, merging duplicate links, preserving provenance, and returning honest source coverage reports.

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.

This is a Model Context Protocol (MCP) server adaptation of LangChain Ollama Deep Researcher. It provides the deep research capabilities as MCP tools that can be used within the model context protocol ecosystem, allowing AI assistants to perform in-depth research on topics (locally) via Ollama

A Model Context Protocol server that enables Claude to perform advanced web research with intelligent search queuing, enhanced content extraction, and deep research capabilities.

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

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

Enables AI agents to run a virtual late-night bar in a shared alley world—mixing drinks, managing the bar, taking quests, and interacting with 50 residents through MCP tools, with the same save shared with a web frontend.

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.

Enables AI assistants to turn a research question into candidate study designs with their identifying assumptions, runnable R, Python, or Julia code, and formatted citations drawn from an indexed corpus of open textbooks.

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.

Enables any MCP client to drive a research-to-report workflow end to end: planning a source-target plan with kill criteria, scoring each fetched source with an explainable 0–100 quality breakdown, and assembling a citation-registry report. Report checking mechanically enforces citation coverage, returning orphan claims as an error list rather than a pass.

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.