"A server for accessing biomedical and life sciences research articles" matching MCP servers:

Enables biomedical research workflows via MCP, including experiment and document search, PDF text extraction, evidence retrieval, and validation with provenance tracking.

Local-first memory server that stores notes, contacts, and future data as a unified entity graph, providing hybrid retrieval (vector + keyword) for AI assistants via MCP.

An MCP server that captures and stores user decisions during AI-agent interactions, offering structured decision memory, cognitive bias detection, and personalized advice from historical patterns.

Enables AI coding agents to run Tavily-powered web searches and asynchronous, cited research through MCP, with tools for focused search, task creation, and status retrieval.

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.

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

Provides structured web search capabilities optimized for technical and software development content via providers like OpenRouter. It enables AI agents to perform research and retrieve relevant technical data in a consistent, programmatic JSON format.

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

An MCP server that performs iterative deep research using Google Gemini 2.5 Flash with search grounding and URL context, producing professional Markdown reports.

Enables AI-moderated interviews that become cited, searchable transcripts, with a repository Q&A tool that returns exact transcript quotes.

Enables AI-powered iterative research using Google Gemini 2.5 Flash with Google Search Grounding, conducting deep dives with configurable depth and breadth to generate comprehensive, professionally structured research reports.

Enables AI agents to perform deep web research by searching, fetching, chunking, retrieving, and synthesizing cited answers from exact source passages via a deep_research tool.

Provides a private set of high-level tools for web research, focused URL investigation, read-only GitHub research, and persistent semantic memory via a Streamable HTTP MCP gateway.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

Enables semantic search across personal PDF paper collections with page-level citations, allowing users to query their library from any MCP-capable client.

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 AI assistants to perform comprehensive research by searching Google, mining Reddit discussions, scraping web content with JS rendering, and synthesizing findings with citations into structured context.

An MCP server that enables saving, retrieving, and managing research content using ChromaDB vector storage and semantic search.

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 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.