AI agent builds a mountain road in DWG from a single prompt
DWG is now a target format for AI agents in the same way Python is a target language. This demo shows the full path: a prompt of a few lines asks for a mountain road through three named locations on real terrain, and the agent works with no human intervention from there.
From prompt to finished DWG
Terrain and routing in Python
It fetches and parses the terrain tile and runs the routing algorithm in Python on its own — then uses the ODA MCP Server to turn the result into CAD geometry.
DWG and PDF output
The output is a single DWG file with the full scene and a technical PDF report on the road, both produced by the agent. The DWG opens and edits as ordinary CAD data in OdaMfcApp or AutoCAD.
Interactive part with STEP MCP Embedded into Open STEP Viewer
- Run Open STEP Viewer, show MCP Plugin setup in File/Options/Plugins/STEP MCP Server
- In Visual Studio Code, Claude Code start command /mcp which shows a list of all available MCP servers
- Open list of tools for STEO MCP
- Open .step file in Open STEP Viewer
- Set appropriate view for hole to set Feature Hole be nicely visible, mark it up with small red circle for highlight cylindrical face of hole
- Enter prompt (see MCP_Movies_Prompts.txt, part 1)
- AI is finding product ID into Semantic Markup, getting its geometry, analyzing it, calculates volume, surface area, center of extents, center of mass, calculates masses for different materials, adds calculated values as user-defined properties to the product
- AI is looking at current snapshot (with red circle as markup), does "click" using select_in_scene MCP tool to pick highlighted face, calculating cylinder radius and depth for creating Hole Feature
- AI is adding a hole feature (green) for picked cylindrical face of hole
- AI is creating informational draughting model with South-East camera. It doesn't contain any PMIs.
- AI is creating informational draughting model with North-East camera, investigates detail and makes informational Leader PMIs with detail parts names
- AI is creating draughting models with Top, Front and Right cameras, investigates holes by using geometric representation for the product and creating appropriate diameter dimensions for their inner and outer radii.
- Show results:
- Created subtrees of SDAI instances for Hole Feature
- Isolate green Hole Feature
- Show newly created user-defined properties for the product
- Show one-by-one created draughting models views with PMIs
Batch part with stand-alone STEP and VSFX MCP servers interaction
AI creates single PDF document with STEP files overview.
- Run stand-alone STEP MCP over HTTPS protocol, show it's connected to the Claude Code AI agent.
- Enter prompt (see MCP_Movies_Prompts.txt, part 2)
- For several JPMI step files in directory
- Upload all files into STEP MCP
- AI is reading all uploaded STEP files for they to be accessed during the session (Semantic Markup is created for them implicitly which is available as MCP Resources "drawing://")
- AI is finding products within readed STEP files and is finding there products with their geometrical representations
- AI is investigating geometric representations and calculates volume, surface area, center of extents and center of masses for geometries in files, adding appropriate user-defined properties for products.
- AI is calculating masses for different materials, recommends materials for parts.
- These values will be used for PDF documentation creation.
- Importing STEP files into VSFX MCP for snapshots for draughting models creation
- AI is taking draughting models camera settings and provide them into VSFX MCP so it can provide snapshots for them, as separate PNG files.
- AI is creating single PDF file with documentation from calculated values and rendered snapshots, PDF contains analysis of parts geometry, recommendations on materials and snapshots with parts and attached PMIs for them.