A Model Context Protocol server providing multi-paradigm simulation capabilities through conversational interfaces. The server supports
If you already use Text2sim, the text2sim mcp server is the piece that lets your assistant work with it directly. A Model Context Protocol server providing multi-paradigm simulation capabilities through conversational interfaces. The server supports Discrete-Event Simulation via SimPy and System Dynamics modeling via PySD and a PySD-compatible JSON.
Text2Sim MCP Server enables Large Language Models to create, validate, and execute simulation models through natural language interfaces. The server processes JSON-structured simulation configurations and returns execution results with comprehensive analytics.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
Domain — specific examples and workflow guidanceConversation — ready templates for session sharingDocumentation — The Documentation tool exposed by this serverThis sits in the knowledge and memory group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Text2sim's toolset — Domain, Conversation, Documentation — is a fair guide to whether it matches your workflow. It is maintained by IamCatoBot; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Text2sim's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Domain | specific examples and workflow guidance |
| Conversation | ready templates for session sharing |
| Documentation | The Documentation tool exposed by this server. |
{
"mcpServers": {
"Text2Sim MCP Server": {
"command": "uv",
"args": [
"--directory",
"PATH_TO_TEXT2SIM_MCP_SERVER",
"run",
"python",
"-m",
"mcp_server"
],
"env": {}
}
}
}Configuration as documented by the project. Restart the client after saving.
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.