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Use natural language to understand, query, and modify Honeybee energy models.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Honeybee-MCP" yet — see the docs or source repo.
Please read this Honeybee building energy model and summarize its rooms, zones, and main energy-related objects.
A structural overview of the model and key objects available for further querying.
Find all exterior wall-related objects in the model and list their names and associated spaces.
A list of matching model objects and their relationships.
Adjust the specified room settings in this Honeybee model based on my instructions, and tell me which objects were changed.
The model is updated, with a summary of what was changed.
Developers, researchers, or designers can ask AI to understand a Honeybee model and quickly inspect its structure and objects. It is useful when they do not want to manually traverse model data.
When specific objects or condition-based matches need to be found in a Honeybee model, users can issue natural-language queries. This helps locate target objects and relationships more quickly.
If model content in a Honeybee building energy model needs to be changed, users can describe the edits in natural language. The tool helps AI operate on and update the model.
It is an MCP tool that lets AI agents understand, query, and manipulate Honeybee building energy models through natural language. Its main purpose is to make model interaction more natural.
It is known to provide its capabilities through the Model Context Protocol, so an MCP-compatible environment is required. The provided material does not specify installation steps, dependencies, or key requirements; see the source repository.
It is specifically focused on Honeybee building energy models, emphasizing understanding, querying, and modifying those model objects rather than general text chat. The provided material does not say whether it supports additional simulation or analysis features.
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