imagin-studio-api-docs-mcp
OfficialServidor MCP de documentación de la API de IMAGIN.studio
Dale a tu asistente de programación de IA acceso instantáneo a toda la documentación de IMAGIN.studio: configuración de CDN, referencias de API, guías de integración y más.
Una herramienta. Un comando. Funciona con todos los principales asistentes de programación de IA.
Inicio rápido
Pega esto en la configuración MCP de tu agente:
{
"mcpServers": {
"imagin-docs": {
"command": "uvx",
"args": ["imagin-studio-api-docs-mcp"]
}
}
}O simplemente pregúntale a tu asistente de IA:
Instala este servidor MCP: https://pypi.org/project/imagin-studio-api-docs-mcp/
Related MCP server: @ragrabbit/mcp
Cómo funciona
Instalar —
uvx imagin-studio-api-docs-mcp(sin clonar, sin venv, sin configuración)Indexar — En la primera ejecución, clona la documentación y crea un índice vectorial local (~30 seg)
Buscar — Tu asistente de IA llama a
search_docspara encontrar la documentación relevanteMantener actualizado — El índice se actualiza automáticamente cuando cambia la documentación original
Todo se ejecuta localmente. Sin claves de API. Sin servicios externos.
Agentes compatibles
Agente | Ubicación de la configuración |
Claude Code |
|
Claude Desktop |
|
Cursor | Settings > Tools & MCP |
Windsurf |
|
VS Code + Copilot |
|
Cline | Panel de servidores MCP |
Zed |
|
Para obtener instrucciones de configuración detalladas para cada agente, consulta la guía de configuración completa en PyPI.
Alternativa: npx
Si tu agente no puede encontrar uvx (común en aplicaciones con interfaz gráfica como Claude Desktop y Cursor):
{
"mcpServers": {
"imagin-docs": {
"command": "npx",
"args": ["-y", "@imagin.studio/api-docs-mcp"]
}
}
}Qué puedes preguntar
Una vez instalado, prueba con prompts como:
"Busca en la documentación de IMAGIN la invalidación de caché de CDN"
"¿Cómo configuro un dominio personalizado con IMAGIN?"
"Encuentra el endpoint de la API para transformaciones de imagen"
"¿Qué formatos de imagen admite IMAGIN.studio?"
Paquetes
Registro | Paquete | Instalar |
PyPI |
| |
npm |
|
Licencia
Apache License 2.0 — ver LICENSE.
Available Tools
1 toolsearch_docsSearch IMAGIN.studio DocumentationARead-onlyIdempotent
Search the official IMAGIN.studio technical documentation, integration guides, and knowledge base.
Use this tool when the user asks 'How do I...' questions, needs explanation on API concepts (CDN, referrers, caching, 360 spinner), or needs to debug integration issues. Rewrite vague queries into specific technical search terms before calling.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language search query. Use specific technical terms rather than vague descriptions. Good: "CDN cache invalidation headers". Bad: "caching stuff". | |
| top_k | No | Number of results to return (1-20, default 5). Use 1-3 for focused lookups, 5 for general questions, 10-20 for broad research. |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint true, idempotentHint true, destructiveHint false. The description adds that it searches specific content types but does not discuss rate limits, authentication, or result format. It adds some context but not rich behavioral detail.
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?
Three sentences, no redundant words. First sentence states purpose, second gives usage examples, third provides query rewriting advice. Front-loaded and efficient.
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 read-only search tool with good annotations and output schema, the description covers when to use and what to search. It could mention authentication scope or result limitations, but overall it's reasonably complete.
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 100% with detailed descriptions for both parameters. The description does not add per-parameter details beyond the schema, so baseline score of 3 is appropriate.
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 searches official IMAGIN.studio technical documentation, integration guides, and knowledge base. This is specific and complete, with no sibling tools to distinguish from.
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?
Explicitly says when to use ('How do I' questions, API concepts, debug issues) and provides guidance to rewrite vague queries into specific terms. This is optimal usage guidance.
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. Dates show when Glama detected each change.
1 tool update
v0.1.23- First observed
search_docs
TDQS
With only one tool, there is no possibility of confusion between different tools. The single tool is clearly described for its specific purpose.
The single tool name 'search_docs' follows a consistent verb_noun pattern, which is clear and predictable.
One tool is minimal and may feel insufficient for a documentation set; however, it might be acceptable if the scope is strictly limited to search. Still, it falls into the 'thin' category.
The tool covers the core search functionality, but lacks additional operations like retrieving a specific document or listing available topics, which could be useful for a documentation server.
Maintenance
Resources
Unclaimed servers have limited discoverability.
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