"Proton Drive" matching MCP servers:

A local MCP server that enables LLMs to securely search and read files within designated Google Drive folders. Supports Google Docs, Google Sheets, PDFs, and plain text with strict folder-scoping via service account authentication.

Enables querying and managing personal/team internal knowledge from sources like Slack, Gmail, and Drive through semantic search and retrieval.

Enables semantic search and retrieval of information from personal and team knowledge repositories including Slack, Gmail, Dropbox, Google Drive, and uploaded files. Allows storing new information for future recall through AI-powered search.

Enables Google# MyData from (JSON (server name is

MCP server for semantic search over Google Drive documents, enabling AI tools to search, list, and retrieve document content.

Enables MCP clients to list and fetch content from Notion pages and Google Drive files, returning normalized documents for downstream RAG ingestion.

This MCP server replicates how a creative strategist gathers context by expanding queries and performing hybrid search against a Google Drive knowledge base, delivering structured, role-categorized context for ad copy and creative briefs.

Enables MCP-compatible reasoning agents to perform read-only discovery, retrieval, and exact search across Google Drive, Docs, Sheets, and Slides through a stateless Cloud Run service.

This MCP server provides comprehensive Google Workspace integration (Gmail, Drive, etc.) with multi-user OAuth. Unique features include RAG-powered natural language to Chat card rendering, runtime Jinja2 macro creation, and dynamic tool management.

Generates, validates, and updates structured research tables by synthesizing multiple AI queries, enabling AI agents to autonomously drive research workflows.

MCP server that integrates Google Drive, RAG, and memory services for context-aware knowledge management, enabling session, project, document, catalog, and knowledge operations for AI assistants.

Search your company's connected knowledge from any AI tool that speaks the Model Context Protocol. Supports querying across sources like Drive, SharePoint, Confluence, Slack, and Notion with permission filtering.

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

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.

Exposes your Google Drive, Slack, GitHub, and Railway to MCP clients with semantic search, per-user permissions, and optional OAuth, allowing natural-language access to your private data and infrastructure.

Enables semantic search and retrieval of personal and team knowledge from connected sources like Slack, Gmail, Google Drive, and Dropbox, with the ability to save new information for future recall.

Enables advanced semantic search and document management by integrating the GroundX API with Claude Desktop and GitHub Copilot. It supports local file uploads, website crawling, and Google Drive synchronization for RAG workflows.

Enables interaction with Rememberizer.ai knowledge repositories to search, retrieve, and store information across sources like Slack, Gmail, and Google Drive. It supports semantic search and agentic queries to access and manage personal or team internal knowledge.

Enables LLM clients to query a comprehensive Midnight knowledge workspace using indexed evidence from code, Confluence, and Google Drive, with source integrity enforcement and audience-specific answer shaping.

Enables interaction with the Unstructured API to manage data workflows, including creating and managing source connectors (S3, Azure, Google Drive, etc.), destination connectors (Weaviate, Pinecone, MongoDB, etc.), and workflows for document processing and data pipelines.