"Python context management and dependency solving in ComfyUI" 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 task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.

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

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.

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.

The URL-Context-MCP MCP Server provides a tool to analyze and summarize the content of URLs using Google Gemini's URL Context capability via the Gemini API. Now also supports optional grounding with Google Search alongside URL Context. The server is designed to follow prompt-only orchestration: con

A server for connecting to a local ComfyUI instance that enables storing and summarizing notes with custom URI scheme support.

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

Compresses, deduplicates, and filters tool outputs to optimize token usage and context window for AI agents.

Provides a bulk_read_files tool that reads specified files and forwards them to a remote backend for summarization, so agents receive concise summaries instead of raw file contents.

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.

A simple notes MCP server that enables creating, listing, and summarizing text notes via resources, tools, and prompts.

Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.

Enables AI assistants to save, load, and search conversation context with AI-powered summarization and auto-tagging. Demonstrates semantic intent patterns and hexagonal architecture for maintainable AI-assisted development.

Summarizes Slack activity and GitLab merge requests with OpenAI to help generate daily standups, weekly reports, or quarterly check-ins.

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

Model Context Protocol server exposing the bankstatementparser library as first-class agent tools for reading bank statements.

Provides clean, bounded web content to AI by filtering HTML noise and optionally summarizing, preventing context window overflow.

Model Context Protocol server for Archive of Our Own: search fanfiction and have an AI read and rank fics for you.

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.