"Using NotebookLM for deep research" matching MCP servers:

MCP server that automates YouTube research by finding viral videos, analyzing transcripts via Google NotebookLM, and generating content ideas and scripts.

An MCP server for deep research that performs search, scraping, synthesis, fact-checking, and persistent memory, enabling users to conduct comprehensive research tasks via Claude.

Enables AI agents to drive Google NotebookLM notebooks as a deep-research workspace: ingesting local PDFs and YouTube videos, cross-checking sources for contradictions, identifying knowledge gaps, generating audio overviews, and exporting Markdown dossiers with BibTeX and APA bibliographies. It operates over the Model Context Protocol inside Google Antigravity IDE, with browser-session authentication handled automatically.

Enables iterative deep research by integrating AI agents with search engines, web scraping, and large language models for efficient data gathering and comprehensive reporting.

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-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.

An MCP server that enhances Brave Search results by using Puppeteer to extract full webpage content and explore linked pages, enabling AI assistants to perform comprehensive web research with configurable depth.

Provides semantic search and document retrieval via OpenAI Vector Store API, extending ChatGPT Deep Research with custom knowledge and tools.

Enables AI assistants to interact with Google NotebookLM, allowing notebook management, source ingestion, deep research, and content generation directly from the terminal or IDE.

Advanced cognitive thinking MCP server with DAG-based thought graph, multiple reasoning strategies, metacognition, and self-evaluation. A significant evolution beyond sequential-thinking MCP, providing structured deep reasoning with graph-based thought management.

MCP server for Google NotebookLM enabling notebook, source, and audio overview management with hybrid metadata storage.

A pure-TypeScript MCP server for Google NotebookLM using the batchexecute RPC protocol. Enables management of notebooks, sources, chat, and artifact generation with no Python dependencies.

Enables deep web search across multiple providers including Google, Bing, Brave, DuckDuckGo, and Perplexity, with support for comprehensive AI-powered research using intelligent multi-engine queries.

Chat with Google NotebookLM via MCP or HTTP REST API for zero-hallucination answers from your documentation. Features persistent sessions, multi-notebook management, and n8n workflow integration.

Enables AI agents to interact with Google NotebookLM for grounded, hallucination-free answers through notebook management, source management, research, and generation tools.

Enables coding and research agents to run paid, cited deep research on AI infrastructure, MCP, and security topics via remote MCP tools, with query-tied excerpt packs and uncited or failed calls billed at $0.

Enables direct integration with Google NotebookLM from MCP clients, allowing agents to query notebooks, manage libraries, and get grounded research answers without manual copy-pasting. Uses browser automation to maintain persistent authentication and provides RAG-style research capabilities within code editors.

MCP server that lets CLI agents (Claude, Codex, Cursor) chat directly with Google NotebookLM for zero-hallucination answers based on user's own notebooks.

MCP server that connects AI agents to Google NotebookLM, enabling natural language interaction with notebooks, including Q&A, source ingestion, and audio overview generation.

MCP server for Google NotebookLM that allows asking questions to notebooks and managing notebook libraries via browser automation (Patchright). Designed for use with Claude Code and any MCP client.