MCP server for Bentley STAAD.Pro via the OpenSTAAD API
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by OpenSTAAD MCP Server.
discover_apiLists available API skills and usage guidance
read_skillsReturns detailed guidance for requested skills
list_instancesLists active STAAD.Pro instances with model paths and versions
execute_codeRuns validated Python code against the connected STAAD.Pro model
get_statusReturns connection state, STAAD version, model path, analysis status
A Model Context Protocol (MCP) server for Bentley STAAD.Pro that enables AI agents like Claude Desktop, Gemini, or VSCode Copilot to interact with your STAAD.Pro models and perform various time-consuming tasks like load cases definition, data extraction, repetitive property setting and more.
This MCP server was introduced as part of Bentley's Infrastructure AI Co-Innovation Initiative to help our users and accounts discover opportunities and innovate faster, while connecting Bentley's unique engineering tool capabilities to their emerging agentic workflows.
openstaad-mcp.mcpb file from the GitHub Releases page..mcpb file.Claude Desktop will install the server automatically. Open a new conversation and ask Claude to interact with your STAAD.Pro model.
Tip: Make sure STAAD.Pro is running with a model open before you start chatting.
TL;DR:
If not already installed, install uv with the command:
Configure your client to start the server in stdio mode with the command:
For stdio: Open the Command Palette β MCP: Add Server... β Command (stdio) and enter the following command:
For http: First, start the server in a terminal:
Look for the generated token and URL in the terminal output. It should look like this:
Then, in VS Code, open the Command Palette β MCP: Add Server... β HTTP URL and enter the URL shown in the terminal (e.g. http://127.0.0.1:18120/mcp). 18120 is the default port, but yours may differ if you have multiple instances running or if you changed the default. Add the header Authorization: Bearer <token> with the token shown in the MCP server terminal.
Use the /mcp add command inside a Copilot CLI session to add the server. See the Copilot CLI documentation for more details.
For stdio transport, use the command:
For HTTP transport, first start the server in a terminal:
Look for the generated token and URL in the terminal output. It should look like this:
Then add the server in Copilot CLI using the URL shown in the terminal (e.g. http://127.0.0.1:18120/mcp). 18120 is the default port, but yours may differ if you have multiple instances running or if you changed the default. Add the header Authorization: Bearer <token> with the token shown in the MCP server terminal.
If you prefer manual setup over the .mcpb bundle, edit the Claude Desktop
config file directly:
%LOCALAPPDATA%\Packages\Claude_<id>\LocalCache\Roaming\Claude\claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/Library/Application Support/Claude/claude_desktop_config.jsonFor stdio transport, use the command:
For HTTP transport, first start the server in a terminal:
Look for the generated token and URL in the terminal output. It should look like this:
Then add the server in Claude Code with the command:
18120 is the default port, but yours may differ if you have multiple instances running or if you changed the default.
For stdio transport, use the command:
For HTTP transport, first start the server in a terminal:
Look for the generated token and URL in the terminal output. It should look like this:
Then add the server in Gemini CLI with the command:
18120 is the default port, but yours may differ if you have multiple instances running or if you changed the default.
The server supports two transport modes:
| Mode | When to use |
|---|---|
| stdio (default) | The MCP client launches the server process directly. Used by Claude Desktop, Claude Code, VS Code Copilot (stdio config). |
| HTTP | The server runs persistently and clients connect over the network. |
| Flag | Default | Description |
|---|---|---|
--transport {stdio,http} | stdio | Transport mode |
--log-level LEVEL | INFO | DEBUG, INFO, WARNING, or ERROR |
--log-file PATH | OS default | Path to log file |
--port PORT | 18120 | [http] TCP port to listen on |
--token TOKEN | - | [http] Bearer token for authentication |
| Tool | Description |
|---|---|
discover_api | Lists available API skills and usage guidance |
read_skills | Returns detailed guidance for requested skills |
list_instances | Lists active STAAD.Pro instances with model paths and versions |
execute_code | Runs validated Python code against the connected STAAD.Pro model |
get_status | Returns connection state, STAAD version, model path, analysis status |
The execute_code tool supports optional server-side file I/O for bulk data workflows.
Instead of passing large datasets through the agent's context window, the server reads/writes
CSV and XLSX files directly and injects the data into the sandbox as the input_data variable.
| Parameter | Description |
|---|---|
input_data_path | Path to a .csv or .xlsx file. The server reads and parses it, then injects as the input_data variable in the sandbox. |
output_data_path | Path where the sandbox return value will be written. The return value must be a list-of-lists (CSV) or a {sheet_name: {columns, rows}} dict (multi-sheet XLSX). |
overwrite | Allow overwriting an existing output file (default false). |
input_data has a stable, extension-specific shape:
input_data[0] and data rows start at input_data[1:].{sheet_name: {"columns": list, "rows": list_of_rows}}.Path containment: File paths must resolve inside a configured allowed boundary before any read/write occurs.
The server supports both client-configured MCP roots and server-configured allowed directories (via --allowed-dirs or user_config.allowed_directories in the manifest).
The server validates paths against these boundaries before any file access.
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