"Using SearxNG for Deep Research" matching MCP servers:

An MCP server that exposes Gemini's Deep Research Agent for comprehensive web research.

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.

MCP server that runs Google Gemini Deep Research using live Chrome session cookies, enabling autonomous web research and cited report generation without an API key.

An AI-powered deep research agent that automates the full research pipeline from web search to structured executive reports using a 4-tool pipeline (search, fetch, cluster, report).

Enables AI assistants to perform deep web research and generate comprehensive reports using a multi-agent divide and conquer approach.

Enables iterative deep web research through MCP clients, using SearXNG search, Crawl4AI parsing, and LLM synthesis.

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.

Enables users to create and refine a research outline, queue report generation in the background, and retrieve progress or completed Markdown reports, with automatic checkpointing so unfinished work can resume after a restart.

45-tool MCP server for video analysis, deep research, content extraction, web search, and Weaviate knowledge storage. Powered by Gemini 3.1 Pro.

MCP server for AI-powered research using Gemini. Provides fast grounded web search, deep autonomous research, URL extraction, and session management.

Comprehensive web research toolkit with 13 tools for searching (via SearXNG), crawling, package discovery, GitHub metrics, error translation, API documentation lookup, data extraction, technology comparison, and service status checking.

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

Enables AI tools to access local crypto market data, run analyses, perform 66-item deep research, search RAG context, and retrieve generated reports and prompts via MCP.

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 fully local, zero-cost autonomous research by planning questions, searching and reading web pages, generating cited summaries or reports, and retaining semantic memory across sessions.

Enables deep research evidence synthesis and citation verification by generating structured research graphs through the Model Context Protocol.

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.

Enables AI agents and MCP clients to run deterministic deep research consensus arbitration by parsing queries, evaluating source authority and contradictions, and returning structured JSON dossiers and telemetry.

An MCP server that provides autonomous, multi-source web research capabilities for AI agents. It delivers comprehensive, validated information through deep research tools while maintaining security and compatibility with various LLM providers.

Enables AI agents to analyze and link citations across multiple research sources, building cross-citation graphs and resolving consensus from conflicting findings. It exposes this capability as a deterministic, zero-dependency MCP server that plugs into Claude Desktop, Cursor, and other MCP-compliant clients.