"CLine MCP Server Information or Setup" matching MCP servers:

Automates setup of local development environments for Python, Node.js, Flutter, Android, and more on macOS and Linux. Can be used as a standalone CLI or as an MCP server for AI assistant integration.

Enables MCP clients to run Cline CLI prompts and isolated repository-wide analyses, returning terminal text responses with model, duration, and usage/cost.

Enables AI assistants to understand lab topologies, follow operational principles, and interact with real network devices through observable terminals while keeping private access information hidden.

Enables running and verifying SPH fluid simulations via MCP tools for case setup, background simulation, result analysis, and quantitative dam-break validation.

Developers: Search your zsh, bash, or fish shell history from Claude Code, Cline, Cursor, Zed, or any MCP client using tools like search_history (full-text with timestamp/CWD/exit code), recent_in_dir, failed_commands, and command_chains for multi-step sequences. Reindex after new activity. Local-only SQLite FTS5 with secrets redacted before storage.

Lets an agent load a design once into a long-lived OpenSTA session and then run static timing and power analysis through dedicated tools or arbitrary Tcl commands. Enables setup/hold slack, TNS/WNS, fmax, DRV, and power queries against the live session.

A minimal MCP server that exposes a single tool to query local hardware information (OS, CPU, memory, architecture).

Stop Package Chaos: Unveil Your Mac’s Setup for Targeted ML Debugging

An MCP server that intelligently filters and compresses tool outputs to reduce context window usage, saving up to 90% of tokens by removing noise such as passing tests and redundant information.

An MCP server for managing the Zopio framework with scenario-based setup, allowing users to install, start, stop, and check status of specific applications like web, API, and email, with Turkish language support and beginner tutorials.

MCP server for driving CESM case lifecycle: setup, build, submit, and monitor. Complements CrocoDash MCP for grid creation and forcing.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Provides Ubuntu system information (CPU, memory, disk, network, services, processes) to Bob via natural language queries.

Enables MCP-based communication with existing interactive terminal channels, such as shells or agent CLIs, by listing, reading, writing text, and sending control signals to tmux sessions without creating or managing them.

A stateless MCP server that wraps the headless Gemini CLI, providing tools to send prompts to Google's Gemini models and receive text responses. It supports both simple prompts and prompts with contextual information.

Enables users to interact with container registries through the ORAS CLI, providing information about container images, platforms, and signatures via natural language queries.

Enables interaction with a running Clojure nREPL instance for evaluating Clojure code, inspecting namespaces, and retrieving connection statuses, compatible with MCP clients like Claude Desktop and CLine in VSCode.

Enables AI assistants to manage Docker containers, execute commands inside them, and inspect container information through a minimalist set of tools supporting both stdio and HTTP transports.

Enables secure SSH access to servers through a gateway with Kerberos authentication, allowing execution of whitelisted commands with pattern-based security controls and server information retrieval.

Gives MCP-compatible AI agents a full local terminal over stdio, enabling shell command execution, file reads and writes, content search, background processes, and stateful tmux sessions with variable capture, auditing, and a configurable command denylist. Requires no deployment or cloud setup.

Voice-driven CFD MCP server that enables natural language setup, execution, and analysis of OpenFOAM simulations, with results exportable to ParaView.

For people who want their AI to run the build, read the error and check the dev server itself, instead of pasting output into chat. Works with Claude Desktop (one-click installer), Cursor, Claude Code and Cline. Runs locally over stdio or HTTP, no telemetry. A seatbelt for everyday mistakes, not a sandbox.

Provides read-only access to native macOS system utilities including disk management, battery status, network configuration, and system profiling through terminal commands. Enables users to retrieve system information and diagnostics from macOS machines via standardized MCP tools.

Enables AI coding agents in Cursor, Claude Code, Cline, and similar editors to halt repetitive failed edits after two consecutive attempts and instead gather falsifiable evidence such as git status, dirty diffs, and locked-port checks before writing more code. It also supervises wrapped shell commands, terminating hung prompts and orphaned process trees so agents can restore a clean, testable baseline.

Provides deterministic system information and developer utilities including date/time operations, OS details, math calculations, random data generation, hashing, text formatting, data validation, encoding/decoding, and log analysis.

Enables AI clients to execute Windows commands, manage files, query system information, and perform code checks via MCP protocol.

MCP server that gives AI coding agents (Claude Code, Cursor, Cline, etc.) access to multiple AI models through Antigravity CLI and OpenAI Codex CLI, enabling mid-conversation model consultation and code review.

Enables remote control and automation of Android devices through the Model Context Protocol, supporting UI interactions, app management, ADB commands, screenshots, and device information retrieval via AutoBot API.

Controls kd.exe for KDNET kernel debugging on Windows, often paired with winrm-mcp for guest VM setup over WinRM.

Enables AI assistants to programmatically generate Huawei eNSP .topo files that include USG6000V firewalls and S3700 switches, and then, once devices are started in eNSP, deliver configurations, run verification, and diagnose faults over Telnet. Ships with one-click health self-checks and topology-generation skills for natural-language-driven lab setup.