revit-mcp
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xml.Revit.MCP Tools Overview
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xml.Revit.MCP provides a comprehensive set of tools for integrating with Autodesk Revit through the Model Context Protocol (MCP). This library serves as a bridge between AI assistants and Revit, enabling powerful automation capabilities and programmatic interaction with building models.
!xml.Revit.png
Key Features
The tool library includes numerous functions for Revit automation and interaction:
Basic Operations:
- Get available commands from Revit plugin
- Execute specified commands in Revit
- Call specific Revit functions with parameters
- Retrieve view data and selected elements
Element Management:
- Find elements by category
- Get element parameters and locations
- Update element parameters
- Delete elements
- Show/highlight elements in current view
- Move elements to new positions
Creation Tools:
- Create levels/floors
- Create floor plan views
- Create grid lines
- Create walls and floors
- Create rooms and room tags
- Create doors and windows
- Create MEP elements (ducts, pipes, cable trays)
- Create family instances
- Link DWG files
- Create sheets
Installation Requirements
- xml.Revit: Version 1.3.4.3 or newer
- Python: 3.10 or newer
- UV Package Manager: Required for installation
- Revit: Compatible with versions 2019-2024 (with plugin)
Installation Process
-
First, install the UV package manager:
pip install uv
-
Install the revit-mcp package:
pip install revit-mcp
-
Test the installation:
uvx revit-mcp
You should see:
RevitMCPServer - INFO - Successfully connected to Revit on startup
Integration with AI Assistants
Claude for Desktop
Edit claude_desktop_config.json
to include:
Cursor
Edit mcp.json
to include:
Cline
Edit cline_mcp_setting.json
to include:
{
"mcpServers": {
"RevitMCPServer": {
"disabled": false,
"timeout": 30,
"command": "uvx",
"args": ["revit-mcp"],
"transportType": "stdio",
"autoApprove": [
"active_view",
"call_func",
"create_cable_trays",
"create_door_windows",
"create_ducts",
"create_family_instances",
"create_floors",
"create_floor_plan_views",
"create_grids",
"create_levels",
"create_pipes",
"create_room_separation_lines",
"create_room_tags",
"create_rooms",
"create_sheets",
"create_walls",
"delete_elements",
"execute_commands",
"find_elements",
"get_commands",
"get_locations",
"get_selected_elements",
"get_view_data",
"link_dwg_and_activate_view",
"move_elements",
"parameter_elements",
"show_elements",
"update_elements"
]
}
}
}
Extending Functionality
You can create custom MCP DLL files to implement additional functionality by:
- Implementing the
xml.Revit.MCP.Public.IMCPMethod
interface - Following JSON-RPC 2.0 specification for communication
- Compiling to a DLL and placing it in the designated MCP folder
Plugin Configuration
When using the revit-mcp-plugin:
- Register the plugin with Revit
- Configure commands through: Add-in Modules → Revit MCP Plugin → Settings
- Enable the service: Add-in → Revit MCP Plugin → Revit MCP Switch
Once enabled, AI assistants can discover and control your Revit program, executing the various commands provided by the xml.Revit.MCP tools library.
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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