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

Provides local, offline searchable access to Roku and BrightScript development documentation via MCP tools and resources, including full-text search, sectioned reading of large docs, and background syncing from the upstream repo.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.

Enables fast literal and regex search over local workspaces using a sparse n-gram index for candidate pruning, with deterministic verification against file contents.

Enables AI assistants to automate WeChat Developer Tools for mini programs, allowing navigation, inspection, and manipulation of pages and components through the miniprogram-automator API.

Unified MCP orchestration layer that consolidates multiple MCPs into a single interface with semantic tool discovery, code-mode execution, scheduling, and intelligent caching to reduce token usage by 97% and eliminate choice paralysis.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Open-source WordPress plugin that turns any site into a Streamable HTTP MCP server. Manage posts, WooCommerce, and more from Claude Code, Codex, or Cursor — no Node.js

MCP server for retrieving FAQ and glossary from the hotline.finance insurance service, supporting both stdio and HTTP modes for integration with clients like Cursor, Claude Desktop, and ChatGPT.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

Enables easy gRPC requests and Protocol Buffer file information retrieval through natural language commands. Supports unary RPCs with SSL, timeout configuration, and response time statistics.

Enables writing to Figma from MCP clients like Claude Code without a Figma Dev seat, using a local WebSocket relay and a Figma dev plugin.

Integrates Cursor AI with Vite Dev server, allowing AI agents to modify code and observe live updates through the Hot Module Replacement system in real-time.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

Deterministic encode, decode, hash and convert for agents, on the same pipeline engine as the String Utility Belt web app, CLI and editor extensions: a pipeline built and checked in the browser runs unchanged from its share link. Base64/hex/URL, JWT, hashes, JSON/YAML/CSV/XML, dates and regex; tools to search, describe and run utilities or whole pipelines, and to detect input formats. Runs locally

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Read-only MCP server for Grafana Loki: lets AI agents (Claude Code, Cursor, Copilot) discover labels, read bounded LogQL pages, count lines by label or time, and export logs — across several Loki stands

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.