"Information about Gmail MCP Node" matching MCP servers:

A TypeScript-based MCP server built on the Gmail API that implements a simple notes system. It enables users to create, manage, and summarize text-based notes through specialized resources and tools.

Enables searching and summarizing emails across multiple Gmail accounts simultaneously through Claude.

Enables AI models to fetch and summarize Gmail messages, send emails with attachments, and convert text content into PDFs. It streamlines email-based workflows like automated reporting and task management through the Model Context Protocol.

Local MCP server that manages Gmail OAuth 2.0 authentication (read-only) and filter setup, with planned AI-driven email digest and summarization features.

A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.

A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.

Generates natural, fluent Chinese content that reads like human writing using the Qwen3-Next-80B-A3B model. Supports web search for latest information and direct file saving with customizable writing rules.

Unofficial MCP server wrapping crawl4ai that enables extraction and analysis of content from web pages, PDFs, Office documents, YouTube videos, and more, with AI-powered summarization and Google search integration to reduce token usage while preserving key information.

Analyzes YouTube videos using Google's Gemini API, allowing users to get summaries or ask questions about video content via direct URL input.

distill-mcp-v2 is a high-performance, network-dependency-free Python FastMCP server designed to aggressively optimize Large Language Model (LLM) context windows. It provides specialized tools for compressing and analyzing massive AI-agent payloads without losing critical semantic information.

MCP server for Glanceway, the macOS menu bar information app, enabling AI assistants to read sources and items.

Enables LLMs to retrieve and analyze Steam game reviews, providing access to review statistics, game information, and helping summarize pros and cons of games.

Enables users to connect to their email inbox via IMAP to search, filter, and summarize emails based on criteria like subject, date, and sender. Supports marking emails as read and provides customizable email summarization with various prompt options.

Wraps the gpt-researcher tool as an MCP server, enabling automated web research, information summarization, and structured report generation via natural language queries.

A production-grade MCP server providing four tools for URL summarization, content repurposing, news digests, and competitor analysis, with cost telemetry and dual transport support.

Enables agents to turn Bilibili course videos into structured VitePress study notes by extracting subtitles, generating organized notes with key points and active recall, and saving them locally. It also supports video search and metadata retrieval through MCP tools.

This MCP server performs multi-topic searches in business, news, finance, and politics using the Tavily API, providing high-quality sources and intelligent summaries.

A Docker-containerized MCP proxy that provides AI image generation, text generation, vision analysis, and text-to-speech capabilities through REST endpoints using Pollinations AI services. Enables multimodal AI interactions including image creation, transformation, OCR, and audio generation through standard HTTP APIs.

Enables AI language models to interact with YouTube content through a standardized interface, providing tools for retrieving video information, transcripts, channel analytics, and trend analysis.

Facilitates note storage and summarization through custom URIs, allowing users to manage, summarize, and update notes with varying detail levels in a collaborative environment.