A
licenseNot graded
qualityD
maintenanceA server that implements the Model Context Protocol, providing a standardized way to connect AI models to different data sources and tools.
7 npm
11
MIT
Compresto MCP
by dqhieu
Compresto MCP
Un servidor de Protocolo de Contexto de Modelo (MCP) para Compresto, que proporciona a los asistentes de IA datos en tiempo real sobre las estadísticas de uso de Compresto.
¿Qué es Compresto?
Compresto es una aplicación de compresión de archivos que ayuda a los usuarios a reducir el tamaño de los archivos. Este servidor MCP permite a los asistentes de IA acceder a estadísticas actualizadas sobre el uso de Compresto.
Related MCP server: RL-MCP
¿Qué es MCP?
El Protocolo de Contexto de Modelo (MCP) es un estándar que conecta los sistemas de IA con herramientas y fuentes de datos externas. Este servidor MCP amplía las capacidades de la IA al proporcionar acceso a las estadísticas de uso de Compresto.
Instalación
git clone https://github.com/dqhieu/compresto-mcp
cd compresto-mcp
npm install
npm run buildConfiguración manual
Agregue lo siguiente a su archivo de configuración de MCP
{
"mcpServers": {
"compresto": {
"command": "node",
"args": [
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/compresto-mcp/build/index.js"
]
}
}
}Cuando se integra con asistentes de inteligencia artificial compatibles, este servidor MCP proporciona datos en tiempo real sobre el uso de Compresto.
Herramientas disponibles
El servidor Compresto MCP proporciona las siguientes herramientas:
obtener-total-usuarios
Devuelve el número total de usuarios de Compresto.
Ejemplo de respuesta: 12345
obtener el total de archivos procesados
Devuelve el número total de archivos procesados por Compresto.
Ejemplo de respuesta: Processed 67890 files
obtener-tamaño-total-reducido
Devuelve la cantidad total de tamaño de archivo reducido por Compresto.
Ejemplo de respuesta: Reduced 1234567890 bytes
Desarrollo
Prerrequisitos
Node.js (v16 o superior)
npm o hilo
Estructura del proyecto
src/index.ts- Punto de entrada principal que contiene la implementación del servidor MCPpackage.json- Dependencias y scripts del proyectotsconfig.json- Configuración de TypeScript
Licencia
Licencia MIT
Available Tools
3 toolsget-total-processed-filesB
Get total processed files of Compresto
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
B3.2/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't reveal any behavioral traits such as whether it's read-only, requires authentication, has rate limits, or what the return format might be. This is a significant gap for a tool with zero annotation coverage.
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 a single, efficient sentence with no wasted words. It's front-loaded with the core purpose, making it highly concise and well-structured.
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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states the purpose but lacks behavioral context and usage guidance, making it incomplete for optimal agent understanding despite the low complexity.
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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, earning a baseline score of 4 for tools with no parameters.
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 ('Get') and resource ('total processed files of Compresto'), providing a specific purpose. However, it doesn't differentiate from sibling tools like 'get-total-size-reduced' or 'get-total-users', which would require explicit comparison to earn a 5.
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 like the sibling tools. There's no mention of context, prerequisites, or exclusions, leaving usage entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-total-size-reducedC
Get total file size reduced of Compresto
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns real-time or historical data, or what format the output is in. The description lacks details on behavioral traits beyond the basic action.
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 a single, concise sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and efficient, though it could be slightly more informative by clarifying terms like 'Compresto' and 'reduced' to improve clarity without sacrificing brevity.
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?
Given the tool has no parameters, no annotations, and no output schema, the description is minimally adequate but incomplete. It explains what the tool does at a high level but lacks details on output format, data scope, or behavioral context. For a simple retrieval tool, this might suffice, but it leaves gaps in understanding the tool's full behavior and usage.
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 tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter information, which is appropriate here. A baseline of 4 is applied since there are no parameters to describe, and the schema fully covers this aspect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Get') and target ('total file size reduced of Compresto'), which is clear but vague. It doesn't specify what 'Compresto' is (e.g., a system, service, or dataset) or what 'reduced' means (e.g., compression, deduplication, or cleanup). It distinguishes from siblings by focusing on size reduction rather than processed files or users, but the purpose remains somewhat ambiguous.
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 its siblings. The description doesn't mention context, prerequisites, or alternatives. While it implies usage for monitoring size reduction metrics, there's no explicit direction on when it's appropriate or how it relates to other tools like 'get-total-processed-files' or 'get-total-users'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-total-usersB
Get total users of Compresto
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
B3.2/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states a read operation ('Get'), implying it's likely safe and non-destructive, but doesn't specify whether it requires authentication, has rate limits, returns real-time or cached data, or details about the output format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is front-loaded and wastes no words, making it easy for an agent to parse quickly.
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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool does but lacks details on behavioral traits and usage context. For a basic read tool, this might suffice, but it doesn't fully address potential agent needs like output format or integration with siblings.
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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter information, which is appropriate here. A baseline score of 4 is given since the schema fully handles parameters, and the description doesn't need to compensate for any gaps.
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 ('Get') and resource ('total users of Compresto'), making the purpose immediately understandable. It distinguishes from siblings by focusing on users rather than files or size reduction, though it doesn't explicitly contrast them. The description avoids tautology by specifying what is being retrieved.
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 like its siblings (get-total-processed-files, get-total-size-reduced). It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage based solely on the tool name and description.
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.
3 tool updates
v1.0.0- First observed
get-total-processed-files - First observed
get-total-size-reduced - First observed
get-total-users
TDQS
B3.2/5.0
Scored across 3 tools
Disambiguation5/5
Each tool has a clearly distinct purpose: one retrieves processed file count, another gets size reduction data, and the third provides user count. There is no overlap in functionality, making it easy for an agent to select the correct tool without confusion.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with hyphens (e.g., get-total-processed-files, get-total-size-reduced, get-total-users). This uniformity enhances readability and predictability across the tool set.
Tool Count3/5
With only 3 tools, the set feels thin for a server named 'Compresto MCP', which might imply broader functionality. However, the tools are well-scoped for reporting metrics, so it's borderline but not severely lacking.
Completeness2/5
The tools only provide read-only metrics (get operations) with no ability to perform actions like processing files, managing users, or configuring settings. This creates significant gaps for a server that might be expected to handle file processing or user management tasks.
Maintenance
ActivityInactive
ResponsivenessNo issues
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