PromptHouse MCP Server

Overview

Prompt House is a purpose‑built MCP server that turns your personal prompt library into an instantly discoverable, AI‑ready resource. Instead of copy‑pasting prompts from notes or spreadsheets into an assistant, the server exposes a set of MCP tools that let any compatible client—Claude Desktop, Cursor, ChatWise, or Cherry Studio—query and retrieve prompts on demand. This eliminates friction in the creative workflow, allowing developers to focus on building higher‑level functionality while the prompt management layer handles storage, tagging, and retrieval.

The server’s core value lies in its tight integration with the Prompt House web or macOS application. By configuring a simple access link, developers can expose their entire prompt collection to the MCP ecosystem without exposing sensitive data to the cloud. The local macOS client stores all prompts on disk, ensuring privacy‑first operation while still offering native support for major model providers and local inference engines like Ollama. For web‑based usage, an NPM package or HTTP bridge provides the same functionality, making it easy to embed Prompt House into custom workflows.

Key capabilities include:

• Prompt Management: A clean UI lets users save, tag, and edit prompts in seconds. Tags enable instant filtering, so the MCP tools can return only relevant prompts based on context or user intent.
• Prompt Calling: Once the MCP connection is established, AI clients can invoke to enumerate all prompts or to fetch a specific prompt by ID. This turns the prompt library into a first‑class API resource, eliminating manual copy‑paste steps.
• Prompt Recommendations: The server ships with a curated collection of high‑quality prompts for productivity, image generation, and more. This feature helps users discover new techniques without leaving the tool.
• Privacy‑First Architecture: Whether running locally on macOS or via a web bridge, the server never transmits raw prompt data to external services. All communication stays within the MCP channel, preserving confidentiality.

Typical use cases span from rapid prototyping—where developers can pull a ready‑made prompt for a new feature—to production systems that dynamically select prompts based on user context. For example, an AI‑powered customer support bot can fetch a pre‑written FAQ prompt when it detects a specific query pattern, ensuring consistent responses. In creative applications, designers can quickly switch between prompts for different styles or themes without leaving their design tool.

Integration is straightforward: developers add a single entry to the section of their client configuration, provide an access link, and optionally set environment variables to tweak mode or enable debugging. Once connected, the MCP tools become available in the client’s prompt palette, allowing seamless invocation through natural language or scripted calls. This plug‑and‑play model empowers developers to build sophisticated, prompt‑driven workflows without reinventing the wheel.