Tekla Structures MCP

v1.0.0APIsstable

A Tekla Structures MCP server designed to accelerate modeling workflows through tool-based automation and natural-language interaction

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What is Tekla Structures MCP?

Tekla Structures MCP is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to tekla structures mcp server designed to accelerate modeling workflows through tool-based automation and natural-language interaction

A Tekla Structures MCP server designed to accelerate modeling workflows through tool-based automation and natural-language interaction

This server falls under the APIs and Cloud Services categories on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • A Tekla Structures MCP server designed to accelerate modelin

Use Cases

Speed up Tekla modeling through tool-based automation.
Use natural language to control Tekla workflows.
Integrate Tekla with AI development assistants.
teknovizier

Maintainer

LicenseGPL-3.0
Languagepython
Versionv1.0.0
UpdatedMay 21, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx tekla

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Tekla Structures MCP

Tekla MCP Server is a Python-based MCP server that bridges AI assistants with Tekla Structures, the industry-leading 3D structural BIM software. It exposes modular toolsets for selection, view management, component insertion, property queries, modeling operations, and drawing management — all accessible through natural language. Structural engineers can describe what they need in plain text and have the AI translate it directly into Tekla operations, dramatically reducing repetitive modeling work.

Prerequisites

  • Python 3.11, 3.12, or 3.13 installed
  • Tekla Structures 2022 or later installed and running with an open model
  • uv package manager installed (https://astral.sh/uv)
  • An MCP-compatible client such as Claude Desktop or Cursor
  • Read access to the Tekla Structures installation directory
1

Clone the repository

Download the Tekla MCP Server source code to your local machine.

git clone https://github.com/teknovizier/tekla_mcp_server.git
cd tekla_mcp_server
2

Install Python dependencies

Install all required packages using uv, the fast Python package manager used by this project.

uv pip install -r requirements.txt
3

Create configuration files

Copy all sample configuration files to their active names. These files control Tekla path, component catalog, element types, semantic attribute overrides, and report properties.

copy config\settings.sample.json config\settings.json
copy config\element_types.sample.json config\element_types.json
copy config\semantic_overrides.sample.json config\semantic_overrides.json
copy config\base_components.sample.json config\base_components.json
copy config\report_properties.sample.json config\report_properties.json
4

Edit settings.json with your Tekla path

Open config/settings.json and set the `tekla_path` property to your actual Tekla Structures binary directory. For example: C:\Program Files\Tekla Structures\2022.0\bin

{
  "tekla_path": "C:\\Program Files\\Tekla Structures\\2022.0\\bin",
  "read_only": false,
  "excluded_tags": [],
  "embeddings": {
    "enabled": true,
    "embedding_model": "teknovizier/minilm-tekla-attr-embed-v1"
  }
}
5

Configure your MCP client

Add the server entry to your MCP client's config file. Replace the placeholder paths with the actual absolute paths on your Windows machine. The server is launched by pointing directly at mcp_server.py.

{
  "mcpServers": {
    "tekla-mcp": {
      "command": "python",
      "args": ["C:\\path\\to\\tekla_mcp_server\\src\\tekla_mcp_server\\mcp_server.py"],
      "env": {
        "TEKLA_MCP_LOG_LEVEL": "INFO",
        "TEKLA_MCP_LOG_FILE_PATH": "C:\\path\\to\\mcp_server.log",
        "TEKLA_MCP_CONFIG_DIR": "C:\\path\\to\\tekla_mcp_server\\config"
      }
    }
  }
}
6

Open Tekla Structures before connecting

Ensure Tekla Structures is running and a structural model is open before starting or connecting your MCP client. The server communicates with a live Tekla instance and will fail if Tekla is not running.

Tekla Structures MCP Examples

Client configuration (Claude Desktop)

Full configuration block for claude_desktop_config.json showing required env vars for the Tekla MCP Server.

{
  "mcpServers": {
    "tekla-mcp": {
      "command": "python",
      "args": ["C:\\Users\\you\\tekla_mcp_server\\src\\tekla_mcp_server\\mcp_server.py"],
      "env": {
        "TEKLA_MCP_LOG_LEVEL": "INFO",
        "TEKLA_MCP_LOG_FILE_PATH": "C:\\Users\\you\\mcp_server.log",
        "TEKLA_MCP_CONFIG_DIR": "C:\\Users\\you\\tekla_mcp_server\\config"
      }
    }
  }
}

Prompts to try

Natural language prompts to send to your AI assistant once Tekla MCP Server is connected.

- "Select all steel beams on grid line A and report their properties."
- "Insert a Lifting Anchor component on the selected concrete slab element."
- "List all available rebar catalog entries for 16mm diameter bars."
- "Change the phase of the currently selected elements to Phase 2."
- "What macros are available in the current Tekla model?"

Troubleshooting Tekla Structures MCP

Server fails to connect to Tekla with a clr or .NET error

There may be a naming conflict with a Python package called `clr`. Rename or delete `C:\Users\<User>\AppData\Local\Programs\Python\Python313\Lib\site-packages\clr` to resolve the conflict, then restart the MCP server.

Tekla is running but the MCP server reports it cannot find the model or connect

Ensure `tekla_path` in config/settings.json points to the correct bin directory for your Tekla version (e.g., C:\Program Files\Tekla Structures\2022.0\bin). For Tekla 2026, verify that `<tekla_path>\Net48Runtime` exists. Restart the MCP server after any settings change — config is read only at startup.

Semantic attribute mapping returns wrong properties

If the MiniLM embedding model fails to download or produces poor matches, set `"embeddings": {"enabled": false}` in settings.json to fall back to LLM-only attribute resolution. The model (~120 MB) downloads automatically on first use from HuggingFace.

Frequently Asked Questions about Tekla Structures MCP

What is Tekla Structures MCP?

Tekla Structures MCP is a Model Context Protocol (MCP) server that tekla structures mcp server designed to accelerate modeling workflows through tool-based automation and natural-language interaction It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Tekla Structures MCP?

Follow the installation instructions on the Tekla Structures MCP GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Tekla Structures MCP?

Tekla Structures MCP works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Tekla Structures MCP free to use?

Yes, Tekla Structures MCP is open source and available under the GPL-3.0 license. You can use it freely in both personal and commercial projects.

Browse More APIs MCP Servers

Explore all apis servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "tekla": { "command": "npx", "args": ["-y", "tekla"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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