MCP Mood Quote Server

Overview

The MCP Mood Quote Server is a lightweight Model Context Protocol (MCP) service that delivers an inspirational quote tailored to a user’s emotional state. By accepting a simple JSON payload containing a mood keyword, the server looks up a pre‑defined collection of quotes and returns one that resonates with that feeling. If the requested mood is not in its catalog, the service gracefully informs the caller that no quote is available. This design keeps the endpoint fast, stateless, and easy to embed in larger conversational AI workflows.

For developers building or extending AI assistants such as Claude, this server solves a common need: injecting emotionally relevant content without requiring the assistant to generate it on‑the‑fly. Rather than relying on a large language model’s sometimes unpredictable output, the service supplies curated, high‑quality quotations. This ensures consistency, reduces hallucination risk, and allows the assistant to focus on higher‑level dialogue management while delegating mood‑specific content delivery to a dedicated microservice.

Key features include:

• Mood‑based lookup: Supports a concise set of moods—happy, sad, tired, excited, angry—each mapped to a carefully chosen quote.
• Stateless HTTP API: Exposes a single POST endpoint that accepts JSON, making it trivial to call from any language or platform.
• Graceful degradation: When an unsupported mood is requested, the server returns a clear message instead of an error, enabling robust client handling.
• MCP compatibility: The service adheres to MCP conventions (message format, tool registration), allowing seamless integration with registries like Nanda and direct use by Claude.

Typical use cases involve conversational agents that want to respond empathetically. For instance, a mental‑health chatbot could query the server when a user expresses frustration and receive a calming quote before offering coping strategies. In creative writing assistants, the service can sprinkle motivational lines at appropriate moments, enhancing user engagement without burdening the main model.

Integrating this server into an AI workflow is straightforward: a client (e.g., Claude) sends a request with the user’s mood, receives the quote, and incorporates it into the generated response. Because MCP tools are invoked via a standardized message format, developers can chain multiple tools—such as sentiment analysis, weather data, and mood quotes—to create rich, contextually aware interactions. The MCP Mood Quote Server’s simplicity, reliability, and emotional relevance make it a valuable addition to any AI‑powered application that seeks to connect with users on a more human level.