fujitsu-sdt-mcp

# Fujitsu Social Digital Twin MCP Server This project integrates [Fujitsu's Social Digital Twin and Digital Rehearsal API](https://portal.research.global.fujitsu.com/converging-technology/) with the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/), allowing Large Language Models (LLMs) to access Fujitsu's Digital Rehearsal API through natural language. ## Overview Fujitsu's Social Digital Twin recreates not only the state of people and objects in the digital space based on real-world data, but also entire economic and social activities. Its core function, "Digital Rehearsal," enables users to simulate human and social behavior in a digital space before implementing measures in the real world, allowing for advance verification of their effects and impacts. This project uses MCP to bridge the gap between LLMs and the Digital Rehearsal API, enabling users to run simulations and analyze results using natural language. ## Key Features - Retrieve and display simulation lists - Start simulations - Retrieve and analyze simulation results - Manage simulation data - Analyze traffic simulations - Compare scenarios - Generate simulation configurations from natural language ## Prerequisites - Python 3.13 or higher - Access to Fujitsu API Gateway (API Key) - MCP-compatible LLM client (e.g., Claude Desktop) ## Installation ### 1. Clone the Repository ```bash git clone https://github.com/3a3/fujitsu-sdt-mcp.git cd fujitsu-sdt-mcp ``` ### 2. Set Up Environment **Using uv (recommended)**: First, install uv: ```bash # Install uv using pip pip install uv # Or using curl (Linux/macOS) curl -sSf https://astral.sh/uv/install.sh | sh ``` Then, set up your environment with uv: ```bash # Create virtual environment uv venv # Activate virtual environment # Windows: .venv\Scripts\activate # Unix/MacOS: source .venv/bin/activate # Install dependencies uv pip install -r requirements.txt ``` Alternatively, you can use the provided setup script: ```bash # Make…