mcp-sentiment-server

# MCP Sentiment Analysis Server This project demonstrates how to build and deploy a Model Context Protocol (MCP) server using Gradio and Hugging Face Spaces. ## 🚀 Overview The application performs sentiment analysis on text input using TextBlob and exposes it as an MCP-compatible tool. This allows both human users and AI agents to access the functionality. ## 🧠 Features - Sentiment analysis (positive / negative / neutral) - Gradio-based web interface - MCP tool exposure for AI clients - Public deployment on Hugging Face Spaces ## 🔗 Live Demo - App: https://hashan-7-mcp-sentiment.hf.space - MCP Schema: https://hashan-7-mcp-sentiment.hf.space/gradio_api/mcp/schema ## ⚙️ Tech Stack - Python - Gradio (with MCP support) - TextBlob - Hugging Face Spaces ## 📦 Installation (Local) git clone https://github.com/hashan-7/mcp-sentiment-server.git cd mcp-sentiment-server python -m venv venv venv\Scripts\activate pip install -r requirements.txt python app.py ## 🧩 MCP Tool The server exposes the following MCP tool: - sentiment_analysis → analyzes text sentiment ## 📌 Use Case This project demonstrates: - Building custom AI tools - Exposing tools via MCP - Deploying AI services to the cloud - Enabling AI agents to discover and use tools dynamically ## 📄 License MIT License