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BentleySystems

OpenSTAAD MCP Server

Official
by BentleySystems
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
discover_apiA

Discover available API guidance and skills.

Call this FIRST before using other openstaad-mcp tools. Then use read_skills with one or more specific skill names to load full guidance.

read_skillsA

Read one or more skills by name.

Use discover_api first to list available skills. Each skill provides domain-specific guidance (e.g. analysis, geometry, loads).

Pass skill names like ["staad-analysis"] or sub-paths like ["staad-steel-design/assets/DESIGN_CODES"] to read reference files within a skill.

list_instancesA

List all running STAAD.Pro instances.

Returns a list of instances with their alias, process ID, currently open file path, and STAAD version. Call this before execute_code when multiple STAAD instances may be running so you can pick the right one. The alias (e.g. staadPro1) is stable for the server session even if the model file changes.

If a version is below the minimum supported (25.0.1), a warning field is included with details about potential data inaccuracies.

get_statusA

Check the connection to a STAAD.Pro instance.

Pass instance (alias from list_instances) to target a specific instance. Omit it when only one instance is running.

Returns connection state, STAAD version, and model path.

execute_codeA

Execute Python code in a sandbox against the OpenSTAAD API (don't forget to call discover_api and read_skills for API guidance).

The sandbox provides pre-connected staad (the OpenSTAAD root object) and input_data (if input_data_path is provided) variables (plus json and math modules). import statements, dir(), getattr(), ... are BLOCKED.

The last expression value or an explicit result = ... assignment is returned as the result. If output_data_path is provided, the sandbox will write the result to the specified file.

Paths must be on the user LOCAL filesystem and inside MCP roots or configured allowed_dirs. On Claude Desktop, users can configure allowed directories in the extension settings and Claude can use the filesystem copy_file_to_claude tool to move files to Claude's filesystem.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.6/5.0

Scored across 5 tools

Disambiguation4/5

discover_api and read_skills are sequential but distinct; list_instances and get_status both report instance state, though one enumerates all instances and the other checks a single connection. No severe ambiguity.

Naming Consistency5/5

All five tools follow a consistent verb_noun snake_case convention (discover_api, read_skills, list_instances, get_status, execute_code), making the pattern predictable.

Tool Count5/5

Five tools is well-scoped for an API execution server: discovery, guidance, instance listing, status check, and code execution. Each tool has a clear role.

Completeness4/5

The workflow from discovering guidance to executing code is covered. Minor gap: no explicit instance selection parameter on execute_code and no model lifecycle tools, but the API sandbox can handle those operations.

Maintenance

ActivityMaintained
ResponsivenessWithin a week

Resources