"Performing Email-Related Operations in Python" matching MCP servers:

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.

A Python MCP server providing AI agents with tools for local knowledge base search, business context retrieval, and text summarization prompt generation.

A simple note-taking MCP server that allows adding notes and summarizing them via a prompt.

An AI tutoring system that runs as an MCP server, allowing Claude to access and interact with your local educational materials to provide personalized tutoring based on your actual course content.

Analyzes meeting transcripts to determine if they could have been emails, returning filler word count, decisions, action items, and a suggested email.

Enables natural language management of Gmail through MCP tools for searching, analyzing, summarizing, drafting, and sending emails, with AI reasoning and user confirmation for actions.

Enables intelligent Gmail management, including email triage, newsletter classification, promotional email cleanup, summarization, filter suggestions, draft replies, and audit logging.

Provides translation capabilities using the DeepL API, supporting text translation between numerous languages, rephrasing, batch translation, document translation, and language detection with formality control.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

Measures AI-detection risk in text and provides a line-by-line rewrite plan to lower the score.

MCP server for koreafilings.com — AI-summarized Korean DART (전자공시) corporate disclosures, paid per call in USDC via the x402 protocol on Base. Tools: get_pricing (free), get_disclosure_summary (0.005 USDC).

Youtube, readable in AI chats.

An MCP (Model Context Protocol) server specialized in deciphering PDF internal structures.

Enables AI agents and MCP clients to browse Roomtone meeting notes, add YouTube or pasted-text sources, generate summaries, ask questions answered from transcripts, and retrieve raw transcript text. Recording itself stays in the Roomtone app, so the server only reads and adds to existing meetings.

23 developer & data API tools for AI agents - IP/DNS/WHOIS/SSL lookups, web scraping & screenshots, text AI (summarize, translate, sentiment, grammar, redact), and dev utilities (hash, UUID, QR, JWT, cron, IBAN/VAT/email validation, breach check).

Analyzes unstructured documents in a local folder, extracting structure and key terms, and supports generating summaries via a host LLM with validated, approval-based report saving.

MCP server for HumanPen that lets AI agents work on real documents (.docx, .pptx, .pdf) — humanizing content to lower AI-detection scores, converting citations, condensing, and translating while preserving formatting, tables, images, and citations.

MCP Long Context Reader is a Python-based toolkit designed to overcome the context window limitations and high costs associated with Large Language Models (LLMs) processing extensive documents. It provides a FastMCP server with multiple, powerful strategies for an LLM agent to 'read' and query long documents without needing to load the entire text into its context window.

Enables users to extract and review Claude's plan reasoning in Claude Code by reading plan files and providing a structured template for decisions, tradeoffs, and assumptions.

Provides accurate meeting transcription with speaker diarization and multilingual support, allowing users to submit audio URLs, poll transcription status, get transcripts, and summarize via MCP tools in their IDE.