mcp-image-compression
compresión de imágenes mcp
Descripción general del proyecto
mcp-image-compression es un microservicio de compresión de imágenes de alto rendimiento basado en la arquitectura MCP (Protocolo de Contexto Modal). Este servicio se centra en proporcionar capacidades de compresión de imágenes rápidas y de alta calidad para ayudar a los desarrolladores a optimizar los recursos de imágenes para sitios web y aplicaciones, mejorando la velocidad de carga y la experiencia del usuario.
Related MCP server: imagic-mcp
Características
Compatibilidad con múltiples formatos : comprime los principales formatos de imagen, incluidos JPEG, PNG, WebP y AVIF.
Uso sin conexión : no es necesario conectarse a Internet para usarlo
Compresión inteligente : selecciona automáticamente los parámetros de compresión óptimos según el contenido de la imagen
Procesamiento por lotes : admite la compresión paralela de múltiples imágenes para una mayor eficiencia
Control de calidad : calidad de compresión personalizable para equilibrar el tamaño del archivo y la calidad visual
HERRAMIENTAS
image_compressionCompresión de imágenes
Entradas:
urls(cadenas): URL de imágenes para comprimirquality(int): Calidad de la compresión (0-100)format(cadena): Formato de la imagen comprimida (por ejemplo, "jpeg", "png", "webp", "avif")
Devuelve: URL de imágenes comprimidas
Configuración
NPX
{
"mcpServers": {
"Image compression": {
"command": "npx",
"args": [
"-y",
"@inhiblab-core/mcp-image-compression"
],
"env": {
"IMAGE_COMPRESSION_DOWNLOAD_DIR": "<YOUR_DIR>"
},
"disabled": false,
"autoApprove": []
}
}
}Construir
docker build -t mcp-image-compression .Licencia
Este servidor MCP cuenta con la licencia MIT. Esto significa que puede usar, modificar y distribuir el software libremente, sujeto a los términos y condiciones de la licencia MIT. Para más detalles, consulte el archivo de LICENCIA en el repositorio del proyecto.
Available Tools
1 toolimage_compressionC
Compress an image
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | URL of the image to compress,If it's a local file, do not add any prefix. array join by ',' | |
| quantity | No | Number of transcripts to return | |
| format | No | Image format |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden to disclose behavioral traits. It says nothing about whether the compression modifies the original, what is returned, rate limits, or supported size limits. The agent has no clue about side effects or constraints.
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 (one phrase), which makes it concise, but it is under-specified. It achieves conciseness at the expense of critical information, so it does not earn its place fully. A balanced description would be more 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 complexity of image compression and the lack of an output schema or annotations, the description is grossly incomplete. It omits information about output format, error handling, supported input types, and the meaning of the 'quantity' parameter. An agent cannot reliably use this tool without further clarification.
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% but the description adds no meaning beyond the schema. Moreover, the 'quantity' parameter's description ('Number of transcripts to return') is confusingly unrelated to image compression, and the description does nothing to clarify this mismatch. Baseline 3 is reduced because the description fails to add value or resolve ambiguity.
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 states the verb 'Compress' and the resource 'an image', which is clear and specific. It is not a tautology and distinguishes the tool's core action. However, it lacks details on supported formats or output behavior, so not a 5.
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, prerequisites, or alternatives. The description simply states what it does without any context for appropriate usage scenarios.
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
v1.0.0- First observed
image_compression
TDQS
Only one tool exists, so there is no ambiguity with other tools.
With a single tool, naming consistency is not applicable; the name is clear and follows a verb_noun pattern.
One tool for image compression is slightly below the typical range but reasonable given the narrow focus.
The single tool only compresses images without apparent options for quality, dimensions, or format conversion, leaving many image operations uncovered.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
MCP server for Qwen Image 3 AI image generation
MCP server for progressive tool usage at any scale (see https://klavis.ai)
MCP server for Wan AI video generation
MCP server for Speech-to-Text
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceAn MCP server providing tools for image processing operations329PythonMIT
- AlicenseAqualityDmaintenanceAbout MCP server for image conversion, resizing, and merging — runs locally, no uploads5161MIT
- AlicenseNot gradedqualityCmaintenanceMCP server for converting images to WebP and AVIF formats with batch processing and parallel execution.MIT
- AlicenseAqualityCmaintenanceLocal image processing MCP server providing background removal, stock media search, resize, format conversion, and collage creation.5MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/InhiblabCore/mcp-image-compression'
If you have feedback or need assistance with the MCP directory API, please join our Discord server