Connects AI agents to Bentley STAAD.Pro's OpenSTAAD API for structural engineering workflows. You can automate repetitive tasks like defining load cases, extracting analysis data, and setting properties across models without clicking through the GUI. Supports multiple STAAD.Pro instances running simultaneously, which helps when you need to parallelize operations across different structural models. Everything runs locally on Windows with no cloud calls. Part of Bentley's Infrastructure AI Co-Innovation Initiative, so it's designed to work with Claude Desktop, VS Code Copilot, and other MCP clients out of the box. Requires STAAD.Pro 2025 or newer to be running with a model open.
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:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Configure your client to start the server in stdio mode with the command:
uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp
For stdio: Open the Command Palette → MCP: Add Server... → Command (stdio) and enter the following command:
uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp
For http: First, start the server in a terminal:
uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp --transport http
Look for the generated token and URL in the terminal output. It should look like this:
WARNING: No --token provided. Auto-generated token: abc123def456ghi789jkl012mno345pq
INFO: Starting MCP server 'OpenSTAAD MCP' with transport 'http' (stateless) on http://127.0.0.1:18120/mcp
Then, in VS Code, open the Command Palette → MCP: Add Server... → 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:
uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp
For HTTP transport, first start the server in a terminal:
uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp --transport http
Look for the generated token and URL in the terminal output. It should look like this:
WARNING: No --token provided. Auto-generated token: abc123def456ghi789jkl012mno345pq
INFO: Starting MCP server 'OpenSTAAD MCP' with transport 'http' (stateless) on http://127.0.0.1:18120/mcp
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.json{
"mcpServers": {
"openstaad": {
"command": "uvx",
"args": ["--from", "git+https://github.com/BentleySystems/openstaad-mcp", "openstaad-mcp"]
}
}
}
For stdio transport, use the command:
claude mcp add --transport stdio openstaad -- uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp
For HTTP transport, first start the server in a terminal:
uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp --transport http
Look for the generated token and URL in the terminal output. It should look like this:
WARNING: No --token provided. Auto-generated token: abc123def456ghi789jkl012mno345pq
INFO: Starting MCP server 'OpenSTAAD MCP' with transport 'http' (stateless) on http://127.0.0.1:18120/mcp
Then add the server in Claude Code with the command:
claude mcp add --transport http openstaad http://127.0.0.1:18120/mcp --header "Authorization: Bearer <your-token>"
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:
gemini mcp add openstaad uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp
For HTTP transport, first start the server in a terminal:
uvx --from git+https://github.com/BentleySystems/openstaad-mcp openstaad-mcp --transport http
Look for the generated token and URL in the terminal output. It should look like this:
WARNING: No --token provided. Auto-generated token: abc123def456ghi789jkl012mno345pq
INFO: Starting MCP server 'OpenSTAAD MCP' with transport 'http' (stateless) on http://127.0.0.1:18120/mcp
Then add the server in Gemini CLI with the command:
gemini mcp add --transport http --header "Authorization: Bearer <your-token>" openstaad 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.
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_path | Path to a .csv or .xlsx file. The server reads and parses it, then injects the data as the immutable input_data variable in the sandbox. |
output_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). |
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.
Limits: Max file size 50 MB, max 100K rows, max 500 columns, max 50 input sheets.
--token MY_SECRET_TOKEN when running in HTTP mode and include Authorization: Bearer <token> in client requests.Host, Sec-Fetch-Site and Origin headers.execute_code tool validates all Python code via
AST analysis before execution. Imports, file access, and dangerous
builtins are blocked.Please find the Bentley Systems privacy policy here.
git clone https://github.com/BentleySystems/openstaad-mcp.git
cd openstaad-mcp
python -m venv .venv
# Windows (PowerShell)
.\.venv\Scripts\Activate.ps1
# Windows (cmd)
.venv\Scripts\activate.bat
pip install -e ".[dev]"
# stdio mode (default)
openstaad-mcp
# HTTP mode
openstaad-mcp --transport http
# All unit tests (no STAAD.Pro needed)
pytest
# Specific test files
pytest tests/test_skills.py tests/test_connection.py -v
# Integration tests (requires a running STAAD.Pro instance on Windows)
pytest -m integration -v
ruff check .
ruff format --check .
.exe files distributed via the installer:pip install -e ".[build]"
pyinstaller mcpb/openstaad-mcp.spec --noconfirm
This creates one file in the dist/ directory:
openstaad-mcp.exe: console executable (stdio & http transport).mcpb installer bundle, run:npm install -g @anthropic-ai/mcpb
New-Item -ItemType Directory -Path mcpb-staging -Force
Copy-Item dist/openstaad-mcp.exe mcpb-staging/
$version = (Select-String -Path pyproject.toml -Pattern '^version\s*=\s*"(.+)"$').Matches[0].Groups[1].Value
$manifest = Get-Content mcpb/manifest.json -Raw | ConvertFrom-Json
$manifest.version = $version
$manifest | ConvertTo-Json -Depth 10 | Set-Content mcpb-staging/manifest.json -Encoding utf8
mcpb pack mcpb-staging/ openstaad-mcp.mcpb
The output MCPB bundle is written to .\openstaad-mcp.mcpb.
See CONTRIBUTING.md for guidelines on setting up your development environment, branch naming, running tests, and submitting pull requests.