"Reading terminal outputs from a Next.js dev server while developing in Cursor" matching MCP servers:

A 4-stage reading companion that helps users set reading goals, discover books, track progress, and deepen learning through reflection, integrated with Claude Desktop.

MCP server that helps AI agents inspect Minecraft project evidence (crash logs, mod files, datapacks) before writing development code.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides AI agents with access to a comprehensive database of 200+ Next.js documentation URLs for intelligent document selection and retrieval. Enables Claude and other AI assistants to analyze user queries and recommend the most relevant Next.js documentation pages.

Enables local EPUB reading with AI agents, supporting annotations, parallel editions, and MCP tools.

A mobile-first AI co-reading MCP server that lets users import novels or comics, sync reading progress with AI, and interact through comments, bookmarks, and notes.

Enables Claude Code or Codex CLI to see the exact sentence and section you are viewing in Chrome, so you can discuss books with context, take notes, and track reading progress.

Enables human-in-the-loop AI development where Trello tickets drive analysis, implementation, commits, and board sync in Cursor.

Enables shared reading between humans and AI assistants, including book import, chunked reading, margin annotations, reading progress tracking, and note exchange.

An AI reading companion that curates next books based on the Chicago Plan curriculum and tracks user reading progress with personal tokens. It offers book recommendations, logging, coaching questions, and reading reports.

A template MCP server built with Next.js using the Vercel MCP Adapter. Provides a framework for deploying MCP servers with custom tools, prompts, and resources on Vercel with SSE transport support.

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

Enables management of visible, interactive terminal sessions across platforms (macOS, Windows, Linux, WSL). Supports creating, executing commands, capturing output, and managing multiple terminal windows simultaneously.

Give AI agents a persistent, interactive terminal with support for SSH, REPLs, database CLIs, TUI apps, and long-running processes.

Provides tools for Cursor to interact with IBM Bob Shell, enabling Bob-powered coding assistance, session management, and task delegation directly from Cursor.

A local MCP server for low-token co-reading: import a book, split it into chapter-sized chunks, read it chunk by chunk, and keep notes so a session can resume without re-reading the whole book.

A local MCP server that gives Claude a durable reading room for EPUB and plain text books, enabling chunk-by-chunk navigation, annotations, progress tracking, and shared margin cards.

Enables a shared reading room where users and Claude can import EPUB or text books, read chunk-by-chunk, annotate passages, search, track progress, and resume from unread sections.

A server that enables AI assistants to execute terminal commands and retrieve outputs via the Model Context Protocol (MCP).

A VSCode and Cursor extension that captures real-time terminal output and exposes it to AI assistants via the Model Context Protocol. It enables agents to proactively monitor logs, command execution, and errors without requiring manual copy-pasting from the user.