Text2Sim MCP Server
JSON →A multi-paradigm simulation engine for Discrete-Event and System Dynamics, enabling natural language-based simulations via MCP.
Tools · 16
- simulate_des Execute Discrete-Event Simulation models. Accepts JSON configuration with entity types, resources, and processing rules. Returns simulation results with metrics and statistical analysis.
- simulate_sd Execute System Dynamics models. Accepts PySD-compatible abstractModel JSON format. Returns time-series data and model execution metadata.
- run_multiple_simulations Execute multiple simulation replications. Runs multiple independent simulation runs with statistical analysis. Returns confidence intervals, variability measures, and reliability scoring. Supports seed-based random number control for reproducible results.
- validate_model Validate simulation model configurations. Supports both DES and SD model validation with auto-detection. Provides detailed error reports with correction suggestions. Multiple validation modes: partial, strict, and structural.
- help_validation Get validation guidance. Shows all available validation tools and when to use each one. Provides troubleshooting guidance for validation errors. Includes schema type detection and validation mode explanations.
- get_schema_help Access comprehensive schema documentation. Returns structured documentation for schema sections with examples. Supports nested section paths (e.g., 'processing_rules.steps'). Multiple detail levels: brief, standard, and detailed. Domain-specific examples and workflow guidance.
- save_model Store models with metadata. Automatic naming with domain detection. Metadata tracking including validation status and tags. Version management with conflict resolution.
- load_model Retrieve stored models. List all saved models with filtering options. Load specific models by name or identifier. Integration with last-loaded state tracking.
- export_model Export models to JSON. Multiple output formats for different use cases. Conversation-ready templates for session sharing. Token count estimation for LLM context management.
- list_templates Browse available model templates. Lists pre-built templates for both DES and SD models. Filter by schema type, domain, or complexity level. Includes template descriptions and use cases.
- load_template Retrieve specific templates. Load template configurations by name or template ID. Returns ready-to-use model configurations. Supports both DES and SD template formats.
- save_template Save models as reusable templates. Store validated models as templates for future use. Automatic template naming with metadata. Template sharing and organization capabilities.
- delete_template Remove user templates. Safe deletion with confirmation requirements. Protects built-in templates from accidental removal. Provides backup recommendations.
- get_sd_model_info Analyze System Dynamics models. Provides detailed analysis of SD model structure without simulation. Returns complexity metrics and variable information. Validates abstractModel format and reports structure analysis.
- convert_vensim_to_sd_json Convert Vensim models to PySD JSON. Converts Vensim .mdl files to PySD-compatible abstractModel format. Handles model translation and format validation. Integration with PySD's Vensim translation capabilities.
- delete_model Safe model deletion. Remove saved models with confirmation requirements. Provides model metadata before deletion. Includes undo suggestions and safety features.
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★ 20 GitHub stars