GH_mcp_server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@GH_mcp_serverAnalyze the 3dm file 'model.3dm'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
GH_mcp_server
GH_mcp_server provides an approach that allows designer to interact with Rhino and Grasshopper directly via LLMs, including to analyse .3dm file, do 3D modeling and generate GHPython automatically in Grasshopper based on user’s guidance.
This project is still under construction — and we’d love your help!
Feel free to open an issue if you encounter bugs or have ideas.
Pull requests are always welcome.
If you're interested in collaborating long-term, feel free to reach out to yizhuod@andrew.cmu.edu — we’d love to have you on the team!

Requirements
Rhino 7 or 8
Install
RhinoPython: https://github.com/jingcheng-chen/RhinoPythonForVscode/tree/master?tab=readme-ov-fileuv# For MacOS and Linux curl -LsSf https://astral.sh/uv/install.sh | sh# For Windows powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Claude Desktop
Related MCP server: cadkit
Installation
1. Clone the repository
git clone git@github.com:veoery/GH_mcp_server.git
cd GH_mcp_server2. Set up the environment
We recommend using uv:
macOS/Linux
uv venv
source .venv/bin/activate
uv pip install -e .Windows
uv venv
.venv\Scripts\activate
uv pip install -e .Make sure the virtual environment is activated before running or developing the project.
3. Configuration
In the Claude Desktop, Navigate to Settings->Developer. You will see
Edit Config.Click the
Edit Configand open the fileclaude_desktop_config.jsonPlace the following code to the json file:
{ "mcpServers": { "grasshopper": { "command": "path_to_GH_mcp_server/.venv/bin/python", "args": [ "path_to_GH_mcp_server/run_server.py" ] } } }Restart the Claude Desktop. If you are able to see a hammer icon, the configuration is successful. Click the hammer icon to check all the attached MCP tools.
Usage
Start Rhino
Type command
CodeListener. You should seeVS Code Listener Started....Open the Claude Desktop and type the prompts to interact with GH_mcp_server tools. Please also check the file
examples\zaha01.ghas a reference for interacting with Grasshopper. Here are some examples:Read the file "D:\test01.3dm" first and analyse the objects in this file.write GHpython to create a tower referring to zaha and write the ghpython code to "D:\zaha01.py"
Available Tools
8 toolsadd_grasshopper_componentC
Add a component from an existing Grasshopper plugin.
Args: component_name: Name of the component component_type: Type/category of the component parameters: Component parameters and settings
Returns: Result of the operation
| Name | Required | Description | Default |
|---|---|---|---|
| component_name | Yes | ||
| component_type | Yes | ||
| parameters | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states the basic action without disclosing behavioral traits such as whether the operation modifies existing definitions, requires prerequisites, or has side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with clear Args and Returns sections, but the Returns section is generic ('Result of the operation'). It is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and three required parameters, the description lacks sufficient context about preconditions, return value details, or interaction with existing data. It is barely adequate for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds minimal value beyond listing parameter names. For example, 'parameters' is described as 'Component parameters and settings,' which is generic and does not clarify structure or expected values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Add a component from an existing Grasshopper plugin.' This verb-resource combination is specific and distinguishes it from sibling tools like 'run_grasshopper_definition' or 'connect_grasshopper_components'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. No when-not or contextual cues are provided, leaving the agent to infer usage solely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
analyze_rhino_fileC
Analyze a Rhino (.3dm) file.
Args: file_path: Path to the .3dm file
Returns: Analysis of the file contents
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It only says 'Analyze' without disclosing side effects, permissions, or specifics about the return value beyond 'Analysis of the file contents'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short and to the point, but it lacks structure and detail. It is under-specified, making it less effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema), the description fails to explain what 'analysis' entails, leaving the agent with ambiguous expectations about the return value and behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It repeats 'file_path' from the docstring but adds no additional semantics (e.g., format, constraints, examples) beyond the schema's basic type definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'analyze' and the resource 'Rhino (.3dm) file'. However, it does not differentiate from siblings like 'list_objects' or 'extract_geometry', which could overlap with analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any prerequisites or context. The description is purely functional.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
connect_grasshopper_componentsC
Connect parameters between Grasshopper components.
Args: source_id: Source component ID source_param: Source parameter name target_id: Target component ID target_param: Target parameter name
Returns: Result of the operation
| Name | Required | Description | Default |
|---|---|---|---|
| source_id | Yes | ||
| source_param | Yes | ||
| target_id | Yes | ||
| target_param | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior, but it only says 'connect parameters' and returns a result. It doesn't mention side effects, error handling, or requirements like components existing, leaving the agent uninformed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence and a parameter list. No extraneous information, but it could benefit from slightly more context without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of connecting components (4 parameters, no output schema, no annotations), the description is incomplete. It lacks context about prerequisites, failure modes, and the nature of the operation, which is insufficient for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should explain parameters. It lists parameter names but provides no additional meaning beyond the names and schema titles, e.g., it doesn't explain what a 'parameter name' refers to in Grasshopper.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Connect parameters between Grasshopper components.' This is a specific verb+resource combination that distinguishes it from sibling tools like add_grasshopper_component or execute_grasshopper_code.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidelines are provided on when to use this tool versus alternatives, nor are there any exclusions or prerequisites mentioned. The description only states what the tool does.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
execute_grasshopper_codeC
Execute given Python code.
Args: code: The given code to execute file_path: Path where the generated code will be saved
Returns: Result of the executing code
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | ||
| file_path | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions execution and file saving but omits critical behavioral traits like security risks, side effects, or return value specifics. 'Result of the executing code' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the core action. It includes sections for Args and Returns without unnecessary text. Could be slightly more efficient but acceptable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a code execution tool that saves to a file, the description lacks important details: execution environment, output format, error behavior, and prerequisites. Without output schema, return value is ambiguous. Incomplete for safe use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description adds value by listing and briefly explaining both parameters. However, explanations are minimal (e.g., 'The given code to execute') and lack details like supported formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Execute given Python code' which specifies a verb and resource. However, it does not distinguish this tool from siblings like 'run_grasshopper_definition', leaving ambiguity about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks any 'when to use' or 'when not to use' context, making it hard for an agent to choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_geometryB
Extract geometric data from an existing object.
Args: file_path: Path to the .3dm file object_index: Index of the object to extract data from
Returns: Geometric data in a readable format
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | ||
| object_index | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully bears the burden of behavioral disclosure. It doesn't state whether the tool is read-only, if it modifies the file, permission requirements, or that it returns a 'readable format' without specifics on structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear Args and Returns sections, and it is appropriately sized. It could be slightly more concise, but the structure aids readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description is incomplete. It doesn't detail the return format, potential errors, or prerequisites, leaving ambiguity for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema coverage, the description provides meaningful parameter descriptions for both file_path and object_index in the Args section, clarifying the file type (.3dm) and the purpose of the index.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool extracts geometric data from an existing object, with specific parameter details for file path and object index. However, it doesn't differentiate from sibling tools like list_objects or analyze_rhino_file, which could have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like list_objects or analyze_rhino_file. There is no mention of prerequisites, when not to use, or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_objectsB
List all objects in a Rhino file.
Args: file_path: Path to the .3dm file
Returns: Information about objects in the file
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action and returns 'Information about objects'. It does not disclose whether it is read-only, performance implications (e.g., for large files), or any side effects. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief (two sentences plus an Args section) and front-loads the purpose. No extraneous information, though the Returns line is vague. Efficient but could be more complete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the basic purpose and parameter. However, the return value is vague ('Information about objects'), which leaves the agent uncertain about the output structure needed for downstream tasks.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no description for 'file_path', but the tool description provides the meaning: 'Path to the .3dm file'. Since schema coverage is 0%, the description compensates well for the single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'List all objects in a Rhino file', using a specific verb ('list') and resource ('objects in a Rhino file'). This distinguishes it from sibling tools like 'analyze_rhino_file' or 'extract_geometry'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives or when not to use it. The description only states what it does, leaving the agent without decision-making context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
measure_distanceB
Measure the distance between two objects in a Rhino file.
Args: file_path: Path to the .3dm file object_index1: Index of the first object object_index2: Index of the second object
Returns: Distance measurement information
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | ||
| object_index1 | Yes | ||
| object_index2 | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only states the basic purpose and parameter types, but omits details like whether the file must be open, units of measurement, or side effects (if any).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a concise docstring with no superfluous text. Each sentence serves a purpose: purpose, args, returns. Structurally clear and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and no annotations; the description only gives vague return info 'Distance measurement information'. Missing details on error handling, return format, or prerequisites. For a simple tool, basic completeness is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so the description adds meaning by explaining parameters: 'Path to the .3dm file', 'Index of the first object', etc. This goes beyond the schema's bare types and titles, though it could specify indexing start (0-based vs 1-based).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Measure the distance between two objects in a Rhino file', providing a specific verb and resource. However, it does not differentiate from sibling tools like 'analyze_rhino_file' which might also measure distances.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, nor any prerequisites or conditions for use. The description is purely functional without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_grasshopper_definitionB
Run a Grasshopper definition.
Args: file_path: Path to the .gh file (or None for current definition) save_output: Whether to save the output output_path: Path to save the output (if save_output is True)
Returns: Result of the operation
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | No | ||
| save_output | No | ||
| output_path | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose all behavioral traits. It mentions optional output saving but does not describe whether the tool modifies the Rhino document, if there are side effects, or if it requires specific permissions. The return value is vaguely described as 'Result of the operation', lacking details on type or content. Potential issues like long execution times are not mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured as a docstring with clearly labeled Args and Returns sections. Each sentence is necessary and conveys essential information without redundancy or extra verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there are three parameters, no output schema, and no annotations, the description is incomplete. It does not explain the nature of the return value, error behavior, performance considerations, or prerequisites (e.g., Rhino must be running, Grasshopper components must be available). Additional details about the execution environment would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context to all three parameters beyond what the input schema provides. It clarifies that 'file_path' being None refers to the current definition, and that 'output_path' is only relevant when 'save_output' is True. This adds conditional logic that is not in the schema. However, it could further specify valid file extensions or output formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Run a Grasshopper definition' which is a verb+resource. It distinguishes from sibling tools like 'add_grasshopper_component' and 'execute_grasshopper_code' by focusing on running a definition file. However, it could be more specific about what 'running' entails (e.g., generating geometry or performing computations).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'execute_grasshopper_code'. The description does not specify prerequisites, when not to use, or how to choose among sibling tools. There is no mention of context such as needing an active Rhino document or the component availability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
8 tool updates
v0.1.0- First observed
add_grasshopper_component - First observed
analyze_rhino_file - First observed
connect_grasshopper_components - First observed
execute_grasshopper_code - First observed
extract_geometry - First observed
list_objects - First observed
measure_distance - First observed
run_grasshopper_definition
TDQS
Scored across 8 tools
Most tools have distinct purposes, but 'execute_grasshopper_code' is ambiguous because it executes Python code, not Grasshopper code, potentially causing confusion with other Grasshopper-related tools.
All tool names follow a verb_noun snake_case pattern, which is consistent. However, 'execute_grasshopper_code' is misleading as it executes Python code, not Grasshopper code, slightly breaking the semantic consistency.
With 8 tools, the server covers core Grasshopper and Rhino operations without being excessive. Each tool serves a clear function within the expected scope.
The tool set lacks creation and modification capabilities for Rhino objects and components. Missing tools for creating new geometry, saving files, or deleting objects, which are essential for a complete workflow.
Maintenance
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