Direwolf
Enables robust data extraction, manipulation, and transformation for BIM applications, specifically Autodesk Revit, to facilitate communication with MCP-compatible AI agents.
About
Direwolf is an experimental, proof-of-concept data analysis framework designed for Autodesk Revit and other BIM applications. It provides a complete framework and protocol for extracting, manipulating, and transforming BIM data, enabling seamless data movement within applications, to external tools, and specifically to MCP-compatible LLM (AI) agents. Comprising a host (Direwolf), a RAM-based database (Wolfden), a server (Hunter), and a specialized data format (Wolfpack), it aims to establish a common language for BIM data across diverse sources and storage solutions, addressing contemporary and future technological challenges in the BIM ecosystem.
Key Features
- Provides a simple, low-level API with a REST/JSON-RCP 2.0 hybrid approach.
- Features a completely RAM-based database (Wolfden) and a dedicated server (Hunter).
- 28 GitHub stars
- Utilizes Wolfpack, an MCP-compatible JSON-RCP 2.0 based data format.
- Includes an URI-based schema for accessing any BIM-related entity, property, or taxonomy.
- Experimental data extraction engine and MCP-based server for BIM applications.
Use Cases
- Establishing a common data language for diverse BIM data sources and storage solutions.
- Facilitating data exchange between BIM software and MCP-compatible AI agents.
- Extracting, manipulating, and transforming data from Autodesk Revit models.