"Search related to CMD (Command Prompt)" matching MCP servers:

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

GoHighLevel MCP server for Claude. 212 tools across 43 modules, including the only programmatic GHL workflow builder (private API, reverse-engineered), funnel + page editor, form builder, pipeline builder, pre-deploy validator, multi-sub-account switching, bulk operations, and full account export. $97 one-time, lifetime updates.

Provides a local MCP interface to query captured, PII-scrubbed prompt telemetry from coding agents and browser chats, enabling time summaries, prompt search, and activity analysis without data leaving the machine.

Provides a structured map of 120 practical AI prompts across 6 business domains, enabling users to quickly generate complete prompts for specific tasks using slash commands or tools.

Enables AI to execute registered system commands across platforms using a stable program + args interface, without requiring shell-specific syntax or tool discovery.

Lets MCP hosts search the public Image3 GPT Image 2 prompt gallery, fetch complete prompts, list categories, and turn rough ideas into structured prompt briefs.

Enables deterministic, read-only design of OpenSora video prompts and shot plans, including prompt diagnosis and access to workflow guides, without generating videos or requiring API keys.

An MCP server that enables AI clients to execute shell, Python, and Node commands on the local machine across platforms.

Local MCP server that uses a local Ollama model to rewrite rough prompt drafts into structured, optimized prompts for paid APIs, saving tokens and improving output quality.

Generates and manages slash commands for AI coding assistants like Claude Code and Cursor, supporting both interactive CLI and programmatic MCP access.

An MCP server that uses Claude 3.5 Sonnet to transform ordinary prompts into structured, professionally engineered instructions for any LLM. It enhances AI interactions by adding context, requirements, and structural clarity to raw user inputs.

Enables AI agents to turn rough or ambiguous requests into clearer, context-aware execution guidance through optimization, inspection, adaptation, evaluation, comparison, context compression, and instruction-building tools while preserving original intent and staying local-first.

Enables dynamic prompt management by automatically discovering and serving markdown prompt files with YAML frontmatter via the Model Context Protocol.

Allows AI assistants to safely execute common Unix/macOS terminal commands through a controlled interface with comprehensive security features.

The control plane for AI prompts that scores, enforces policy, locks config, and audits every prompt decision.

Manages AI prompts stored in Notion databases, enabling search, retrieval, and management across multiple prompt collections.

Enables AI models like Claude to manage local prompt files with CRUD operations, fuzzy search, categorization, templates, version control, and favorites.

An MCP server that registers customizable prompt templates as tools for natural language interaction. It supports hot-reloading and easy extension via YAML or JSON files to automate tasks like code review, refactoring, and content summarization.

Enables security researchers to evaluate AI system defenses against prompt injection attacks through a comprehensive set of test vectors and analysis tools.