OpenSTAAD MCP Server MCP Server

OpenSTAAD MCP Server

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.

Key Features

• Fast and flexible: Enjoy minimal latency, interact with every STAAD.Pro features covered by the OpenSTAAD API.
• AI-friendly: Provides documentation, guidance and feedback via dedicated tools to help your AI agent ramp up quickly on the STAAD.Pro API.
• Multi-instance support: Connects to multiple running STAAD.Pro instances simultaneously to parallelize tasks across models.
• Privacy-first: All processing happens locally on your machine. No data is sent to the cloud. No telemetry.

Prerequisites

• OS: Windows 11 or newer
• STAAD.Pro 2025 or newer installed and running

Quick Start with Claude Desktop (<2min)

1. Download the latest openstaad-mcp.mcpb file from the GitHub Releases page.
2. Open Claude Desktop.
3. Click the ☰ menu (top-left) → File → Settings → Extensions.
4. Click Advanced → Install Extensions.
5. Select the downloaded .mcpb file.
6. Click the ☰ menu (top-left) → File → Exit
7. Restart Claude Desktop.

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.

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Other Clients & Configuration

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

VS Code with GitHub Copilot

• 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.

GitHub Copilot CLI

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.

Claude Desktop (manual configuration)

If you prefer manual setup over the .mcpb bundle, edit the Claude Desktop config file directly:

• Windows (MSIX): %LOCALAPPDATA%\Packages\Claude_<id>\LocalCache\Roaming\Claude\claude_desktop_config.json
• Windows (classic): %APPDATA%\Claude\claude_desktop_config.json
• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "openstaad": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/BentleySystems/openstaad-mcp", "openstaad-mcp"]
    }
  }
}

Claude Code (CLI)

• 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.

Gemini CLI

• 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.

Transport Modes

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.

CLI Options

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

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Available MCP Tools

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

File I/O

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:

• CSV: a list of row lists. If a header is detected, it is input_data[0] and data rows start at input_data[1:].
• XLSX: a dict: {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.

Limits: Max file size 50 MB, max 100K rows, max 500 columns, max 50 input sheets.

Security Notes

• Bearer token authentication. Pass --token MY_SECRET_TOKEN when running in HTTP mode and include Authorization: Bearer <token> in client requests.
• DNS rebinding protection. Starlette Middlewares validate Host, Sec-Fetch-Site and Origin headers.
• Code sandbox. The execute_code tool validates all Python code via AST analysis before execution. Imports, file access, and dangerous builtins are blocked.

Privacy Policy

Please find the Bentley Systems privacy policy here.

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Development Setup

1. Clone the repository

git clone https://github.com/BentleySystems/openstaad-mcp.git
cd openstaad-mcp

2. Create a virtual environment

python -m venv .venv

# Windows (PowerShell)
.\.venv\Scripts\Activate.ps1

# Windows (cmd)
.venv\Scripts\activate.bat

3. Install in editable mode with dev dependencies

pip install -e ".[dev]"

4. Run the server from source

# stdio mode (default)
openstaad-mcp

# HTTP mode
openstaad-mcp --transport http

5. Run tests

# 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

6. Lint

ruff check .
ruff format --check .

7. Building the MCPB Bundler

1. To produce the standalone .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)

2. To create the .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.

Contributing

See CONTRIBUTING.md for guidelines on setting up your development environment, branch naming, running tests, and submitting pull requests.