"Google Chrome Browser Information or Downloads" matching MCP servers:

Enables searching Google Scholar with Scholar operators, year ranges, cited-by and all-versions lookups, and retrieving citations in five styles with BibTeX and EndNote export links as structured JSON.

A TypeScript-based MCP server that implements a simple notes system, allowing users to create, access, and generate summaries of text notes through Claude Desktop.

This server provides a note storage system with a custom URI scheme, allowing users to add and summarize notes, with adjustable summary detail levels.

Enables comprehensive management of Google Ads accounts by allowing users to create campaigns, manage keywords, and generate performance reports through a context-aware interface. It features a three-layer architecture that integrates product knowledge and historical campaign data to support intelligent decision-making.

Implements an MCP server that interacts with Google Sheets to store and retrieve prompts and ideas, allowing management of textual content with metadata across spreadsheet tabs.

Comprehensive integration with Google Workspace services (Gmail, Calendar, Sheets, Docs, Drive) plus local storage for job tracking and a personal memory system for storing user preferences, behaviors, and goals.

AutoMem MCP provides persistent memory for AI assistants, enabling them to recall information across conversations and platforms with graph-vector retrieval.

An MCP server that enables Claude to interact with Google NotebookLM via browser automation, allowing management of notebooks, adding sources, and querying information.

A local-first, privacy-first MCP server that passively indexes personal digital activity (screenshots, clipboard, notes, downloads, links) into a local database, enabling LLMs like Claude to access your context without cloud storage.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Provides persistent context management for AI agents by storing and querying semantic information using Upstash Vector DB and Google AI embeddings. It enables semantic search, batch operations, and metadata filtering to help agents retrieve relevant stored knowledge.

Enables AI agents to record, recall, correct, and forget evidence-backed factual claims with temporal history, while explaining whether remembered information is current, historical, or contested.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

Enables AI agents to query and interact with Google NotebookLM notebooks to retrieve citation-backed information. It provides tools for listing notebooks, accessing source data, and asking natural language questions.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Enables building and managing knowledge workspaces with tools for ingesting content from text, clipboard, or URLs and searching organized knowledge bases. Supports multiple configurable workspaces with separate inbox and knowledge directories for structured information management.

An MCP server that gives AI agents a private, durable memory of people, providing a personal people graph in PostgreSQL with tools to search, remember, and connect people, plus imports from LinkedIn, Google Contacts, and WhatsApp, and a browser UI.

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

Enables storing durable AI memories linked to local JSON or text sources, automatically superseding outdated structured values, flagging ambiguous changes for review, excluding expired information, and preserving revision history in a local SQLite database.

Enables interaction with the RAGFlow API to manage knowledge base datasets and conduct AI-driven chat sessions. Users can list datasets, create chat assistants, and retrieve or query information from specialized knowledge bases.