GH_mcp_server

by veoery

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
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.
Naming Consistency4/5
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.
Tool Count5/5
With 8 tools, the server covers core Grasshopper and Rhino operations without being excessive. Each tool serves a clear function within the expected scope.
Completeness2/5
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.
Average 3/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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.
Conciseness3/5
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.
Completeness2/5
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.
Parameters2/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior2/5
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.
Conciseness4/5
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.
Completeness2/5
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.
Parameters2/5
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.
Purpose5/5
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.
Usage Guidelines2/5
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.
Behavior2/5
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.
Conciseness4/5
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.
Completeness2/5
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.
Parameters2/5
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.
Purpose5/5
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.
Usage Guidelines2/5
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.
Behavior2/5
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.
Conciseness4/5
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.
Completeness2/5
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.
Parameters3/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior2/5
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.
Conciseness4/5
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.
Completeness2/5
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.
Parameters4/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior2/5
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.
Conciseness5/5
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.
Completeness2/5
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.
Parameters4/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior2/5
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.
Conciseness5/5
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.
Completeness2/5
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.
Parameters4/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior2/5
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.
Conciseness4/5
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.
Completeness3/5
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.
Parameters4/5
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.
Purpose5/5
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.
Usage Guidelines2/5
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.

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