Fujitsu Social Digital Twin MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| FUJITSU_API_KEY | Yes | Your API key for the Fujitsu API Gateway | |
| FUJITSU_API_BASE_URL | No | The base URL for the Fujitsu API Gateway | https://apigateway.research.global.fujitsu.com/sdtp |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_simulationsC | Returns a comprehensive list of all traffic simulations in the system, including their IDs, names, status, and execution timeframes. |
| start_simulationB | Launches a new traffic simulation using the provided simulation dataset configuration, returning the simulation ID and initial status. |
| get_simulation_resultB | Retrieves the complete results and output files from a finished traffic simulation, including simulation status and generated result files. |
| get_metricsC | Retrieves comprehensive metrics and analytics data from a completed simulation, including travel statistics, emissions data, and traffic flow information. |
| list_simdataC | Returns a complete list of all simulation datasets available in the system, which can be used as inputs for running new simulations. |
| get_simdataC | Retrieves the complete configuration and parameter set for a specific simulation dataset, including region settings, time ranges, and scenario parameters. |
| analyze_traffic_simulationC | Conducts comprehensive analysis on simulation results, providing insights on traffic patterns, bottlenecks, and optimization opportunities for the specified parameters. |
| compare_scenariosB | Performs detailed comparative analysis between two simulation scenarios, highlighting differences in traffic flow, emissions, travel times, and other key metrics. |
| create_natural_language_simulation_configC | Converts a natural language description into a structured simulation configuration, interpreting user requirements into technical parameters for traffic simulation. |
| create_simulation_from_usecaseC | 指定されたユースケースとアップロードされたファイルからシミュレーションを作成・実行します。 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| traffic_simulation_template | Traffic simulation analysis template. |
| escooter_optimization_template | E-scooter optimization analysis template. |
| scenario_comparison_template | Scenario comparison analysis template. |
| usecase_data_preparation | ユースケース別のデータ準備ガイド |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| resource://digital_rehearsal_overview | |
| resource://simulation_metrics_explanation | |
| resource://usecase_requirements |
TDQS
Scored across 10 tools
Most tools have clearly distinct purposes, with clear separation between listing resources, launching simulations, retrieving results, and analyzing scenarios. There is some potential overlap between get_simulation_result, get_metrics, and analyze_traffic_simulation, and between start_simulation and create_simulation_from_usecase, but the descriptions are sufficiently different to guide correct use.
Tool names consistently use a verb_noun pattern, with familiar prefixes like list_, get_, create_, start_, analyze_, and compare_. Minor inconsistencies exist, such as the abbreviated simdata instead of simulation_data and the use of both start_ and create_ for launching simulation workflows.
Ten tools is a well-scoped number for a traffic simulation digital twin server. The set covers dataset discovery, simulation configuration, execution, result retrieval, metrics, and analysis without feeling bloated or redundant.
The tool set covers the core simulation lifecycle well: browse datasets, get dataset details, create configs, start simulations, retrieve results, analyze metrics, and compare scenarios. Obvious lifecycle gaps such as stopping, cancelling, or deleting simulations are not covered, but these are not critical for the primary workflows.