"Using an MCP server to retrieve logs from a terminal for cursor" matching MCP servers:

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

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Scoped, low-latency persistent memory layer for AI agents, Cursor, and Claude Code over Model Context Protocol with sub-50ms hybrid search.

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.

BTC Decision Terminal for AI Agents — live vault-backed Hyperliquid signals, on-chain proof, cross-chain swap. MCP server hosted at https://hypernatt.com/mcp/protocol. 11 tools. Verify in real time.

A Model Context Protocol (MCP) server for Cursor IDE that simplifies the installation and configuration of other MCP servers.

MCP server for Python JSON logs

An MCP server integration that enables Cursor AI to communicate with Figma, allowing users to read designs and modify them programmatically through natural language commands.

Searches Reddit for answers to questions and saves Q&A sessions to Notion.

A secure server for executing terminal commands within predefined paths, allowing safe interaction by Large Language Models with operating system environments.

A secure terminal execution server that enables controlled command execution with security features and resource limits via the Model Context Protocol (MCP).

Provides cross-platform terminal access through MCP, enabling AI assistants to create and manage interactive terminal sessions, execute commands, and capture visual snapshots on Windows, Linux, and macOS.

Acts as a bridge between Claude's desktop application and the Cursor editor, enabling seamless AI-powered automation and multi-instance management across platforms with standardized communication and secure token-based authentication.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Interactive, persistent terminal sessions for AI assistants via Model Context Protocol.

Enables an agent to run shell commands through a JupyterLab/JupyterHub-hosted terminal, using REST API and WebSocket via Selenium for session handling, when SSH is not available.

Enables searching through vectorized Cursor IDE chat history via a FastAPI service powered by LanceDB and Ollama.

Provides AI agents with persistent, interactive pseudo-terminal sessions for running CLI tools, SSH, and AWS SSM, including support for prompts, concurrent commands, and a live web TUI.