MCP Geometry Server
@luorivergoddess/mcp-geo
Un servidor MCP (Protocolo de Contexto de Modelo) para generar imágenes geométricas precisas con Asymptote. Este servidor permite que los modelos de IA compatibles con MCP soliciten la generación de imágenes mediante el código de Asymptote.
Prerrequisitos
Antes de utilizar este servidor, asegúrese de tener instalado lo siguiente:
Node.js : Se recomienda la versión 16.x o superior. Puede descargarla desde nodejs.org .
Asíntota : Esta es una dependencia crítica. La herramienta de línea de comandos
asydebe estar instalada y accesible en la ruta del sistema.Visita el sitio web oficial de Asymptote para descargar e instalar instrucciones detalladas.
Métodos de instalación comunes:
macOS (a través de Homebrew):
brew install asymptoteDebian/Ubuntu Linux:
sudo apt-get install asymptoteWindows: Suele instalarse como parte de distribuciones de TeX como MiKTeX o TeX Live. Asegúrese de que el directorio
binde Asymptote esté añadido a su PATH.
El servidor intentará verificar
asy -versional iniciarse e imprimirá un error si no lo encuentra.
Related MCP server: GGB Web MCP
Instalación
Para instalar este paquete globalmente (si desea ejecutar el comando connect directamente) o como una dependencia en otro proyecto:
npm install @luorivergoddess/mcp-geoSi ha clonado el repositorio y desea ejecutarlo localmente para el desarrollo:
Clonar el repositorio.
Instalar dependencias:
npm installConstruya el proyecto:
npm run build
Uso
Iniciando el servidor
Una vez instalado el paquete (por ejemplo, globalmente o vinculado localmente), puede iniciar el servidor MCP mediante el comando connect incluido en este paquete. Este comando está diseñado para ser invocado por un cliente MCP.
npx @luorivergoddess/mcp-geo connectO bien, si ha clonado el repositorio y lo ha creado:
node dist/cli.jsEl servidor se iniciará y escuchará los mensajes JSON-RPC en stdin/stdout, utilizando @modelcontextprotocol/sdk .
Integración de clientes MCP
Configure su cliente compatible con MCP (p. ej., VS Code con Copilot Agent Mode, Claude Desktop) para usar este servidor. Esto suele implicar indicarle al cliente cómo iniciar el servidor, lo cual se lograría con el comando npx @luorivergoddess/mcp-geo connect .
Herramienta disponible: renderGeometricImage
El servidor expone una herramienta principal:
Nombre:
renderGeometricImageDescripción: Representa una imagen a partir del código Asymptote.
Esquema de entrada:
{ "type": "object", "properties": { "asyCode": { "type": "string", "description": "A string containing complete and valid Asymptote code to be compiled. The server executes this code directly. Ensure necessary `import` statements (e.g., `import graph;`) and settings (e.g., `unitsize(1cm);`) are included within this code block if needed." }, "outputParams": { "type": "object", "description": "Optional parameters to control the output image.", "properties": { "format": { "type": "string", "enum": ["svg", "png"], "description": "The desired output image format. \"svg\" for scalable vector graphics (recommended for diagrams and plots), \"png\" for raster graphics. Defaults to \"svg\" if not specified." }, "renderLevel": { "type": "number", "description": "For PNG output only. Specifies the rendering quality (supersampling level for antialiasing). Higher values (e.g., 4 or 8) produce smoother images but take longer to render and result in larger files. Asymptote default is 2. This server defaults to 4 if not specified and format is \"png\". Ignored for SVG output." } } } }, "required": ["asyCode"] }Salida: La herramienta devuelve un
CallToolResultque contiene una matriz de partes de contenido.Si tiene éxito, incluye una parte
ImageContentcon:type: "image"mimeType: "image/svg+xml"o"image/png"data: "<base64_encoded_image_data>"
También puede incluir una parte
TextContentcon registros de Asymptote.Si ocurre un error, se lanza un
McpError.
Ejemplo de llamada renderGeometricImage (JSON para el campo arguments ):
{
"asyCode": "draw(unitsquare); fill(unitsquare, lightblue);",
"outputParams": {
"format": "png",
"renderLevel": 4
}
}Notas de compatibilidad del cliente:
Algunos clientes MCP pueden tener limitaciones en los tipos MIME de imágenes admitidos.
Por ejemplo, si utiliza este servidor con un cliente que no admite
image/svg+xml(p. ej., ciertas versiones o configuraciones de "Cherry Studio", como se ha informado), asegúrese de solicitar el formatopngincluyendo"outputParams": { "format": "png" }en los argumentos de la herramienta. El servidor usasvgpor defecto si no se especifica ningún formato.
Autor
diosa luoriver
Licencia
ISC
Available Tools
1 toolrenderGeometricImageB
Renders an image from Asymptote code.
| Name | Required | Description | Default |
|---|---|---|---|
| asyCode | Yes | A string containing complete and valid Asymptote code to be compiled. The server executes this code directly. Ensure necessary `import` statements (e.g., `import graph;`) and settings (e.g., `unitsize(1cm);`) are included within this code block if needed. | |
| outputParams | No | Optional parameters to control the output image. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool 'Renders an image' and implies execution of code, but it doesn't mention behavioral traits like error handling (e.g., what happens with invalid code), performance (e.g., rendering time), or output specifics (e.g., image dimensions). The description is minimal, leaving gaps in transparency for a code-execution tool.
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 a single, efficient sentence: 'Renders an image from Asymptote code.' It is front-loaded with the core purpose and has zero waste, making it highly concise and well-structured for its simplicity.
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 (code execution with optional parameters), no annotations, and no output schema, the description is incomplete. It doesn't cover output details (e.g., what the image looks like, error responses) or behavioral aspects. However, the schema provides good parameter documentation, so it's minimally adequate but lacks context for a tool that executes external code.
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 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond the schema's details on 'asyCode' and 'outputParams'. It doesn't explain parameter interactions or provide examples, so it meets the baseline for high schema coverage without compensating value.
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 purpose: 'Renders an image from Asymptote code.' It specifies the verb ('Renders') and resource ('image'), and while there are no sibling tools to distinguish from, the description is specific about the input type (Asymptote code). However, it doesn't mention what kind of image is produced (e.g., geometric diagrams, plots) beyond the Asymptote context, which could be more precise.
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, as there are no sibling tools mentioned. It lacks context about typical use cases (e.g., generating diagrams for documentation, creating plots) or prerequisites (e.g., needing valid Asymptote syntax). Without siblings, the score is based on the absence of any usage context or exclusions.
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.
1 tool update
- First observed
renderGeometricImage
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clearly defined purpose that cannot be confused with any other tool in the set.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'renderGeometricImage' follows a clear verb_noun pattern, and there are no other tools to compare it against for inconsistency.
A single tool is too few for a server named 'MCP Geometry Server', which suggests a broader scope in geometry. This minimal set feels thin and incomplete, likely requiring agents to rely heavily on other servers for basic geometric operations.
The tool surface is severely incomplete for a geometry domain. It only provides image rendering from Asymptote code, missing obvious operations like calculating areas, distances, transformations, or generating geometric shapes, which are fundamental to geometry.
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