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

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

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

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.

Enables progress-triggered text-to-speech in Cursor Agent, with speak and stop controls and voice matching the system UI language.

Enables AI models to run interactive tmux terminal sessions that a human can watch and type into, with all output logged and split into searchable per-command regions so only needed lines enter context. Also guides models through unfamiliar tools by returning exit statuses and key output alongside advice on the tool being used.

A FastMCP server for Cursor platform APIs enabling spend guardrails, cloud agent monitoring, and inter-agent inbox messaging.

Lets ChatGPT, Claude Desktop, Claude Code, and other MCP clients run an allowlisted set of local commands and read files from a chosen directory, so an assistant can analyse a codebase or trigger local generators (images, sprites, assets) without metered API tokens. The server is read-only and deny-by-default by default, with no shell, path containment, opt-in writes, and required auth when exposed over HTTP.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

An MCP server for creating and managing shared terminal progress bars from AI agents, enabling real-time tracking of parallel tasks.

Enables exporting Apple Safari Reading List entries to JSON and adding new items via MCP on macOS.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables AI agents to open persistent interactive terminal sessions with network devices over SSH, Telnet, TCP console, or serial, write raw commands including nested ssh/telnet transitions, and read full output without requiring a particular prompt format. It supports multiple concurrent sessions and keeps credentials/secrets out of MCP arguments or audit logs.

Enables interactive feedback with image support in Cursor, allowing users to paste images for visual context and feedback.

Enables AI agents to run shell commands, execute Python code, read and write files, search text, and create or delete folders through MCP stdio tools.

Enables MCP clients to observe and, when explicitly enabled, send constrained input to whitelisted tmux sessions, with support for local STDIO and loopback-only HTTP transport behind an authenticated tunnel.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Local + remote terminal interaction control MCP Server. Lets AI agents control interactive TUI programs the way a human would.

An MCP server that gives Jan AI terminal and code execution capabilities, enabling shell commands, multi-language code execution, file manipulation, and git operations locally.

An MCP server that enables AI coding assistants to interact with a local Airflow cluster via its REST API for triggering DAG runs, monitoring status, reading logs, and diagnosing errors.