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klara-research

MCP Log Reader

by klara-research
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TypeScript
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Servidor MCP: analizar y depurar registros de MCP

🎯 Descripción general

El Lector de Registros de MCP es un servidor MCP especializado que le ayuda a analizar y depurar los registros del Protocolo de Contexto de Modelo. Proporciona a Claude acceso directo a los archivos de registro, lo que facilita la resolución de problemas de integraciones de MCP y la comprensión de cómo Claude interactúa con sus herramientas.

  • Compatibilidad con múltiples plataformas : funciona en macOS, Windows y Linux con rutas de registro específicas de la plataforma.

  • Filtrado inteligente : encuentre entradas de registro específicas con búsqueda de texto que no distingue entre mayúsculas y minúsculas

  • Navegación paginada : navegue eficientemente por grandes colecciones de registros

  • Gestión de tamaño : gestiona archivos de registro grandes con truncamiento inteligente

  • Integración perfecta con Claude : funciona directamente con Claude Desktop

Related MCP server: Log Analyzer MCP

🚀 Inicio rápido

Instalar directamente desde GitHub:

# Clone the repository
git clone https://github.com/klara-research/MCP-Analyzer.git
cd MCP-Analyzer

# Install dependencies
npm i

Construir y ejecutar:

# Compile TypeScript
npx tsc

🔌 Conectando con Claude

Agregue el servidor a su configuración de Claude Desktop:

{
  "mcpServers": {
    "log-reader": {
      "command": "node",
      "args": [
        "/absolute/path/MCP-Analyzer/build"
      ]
    }
  }
}

Luego reinicie Claude Desktop.

📋 Parámetros disponibles

El lector de registros admite estos parámetros:

Parámetro

Descripción

Por defecto

lines

Número de líneas a leer de cada archivo de registro

100

filter

Texto para filtrar las entradas del registro (sin distinguir entre mayúsculas y minúsculas)

""

customPath

Ruta personalizada al directorio de registro

Específico del sistema operativo

fileLimit

Número máximo de archivos a leer por página

5

page

Número de página para paginación

1

💡 Ejemplo de uso

Pídale a Claude que utilice la herramienta de lectura de registros:

Can you check my MCP logs for any connection errors in the last day?

O con parámetros específicos:

Can you look through MCP logs with filter="error" and lines=50 to find initialization issues?

⚙️ Cómo funciona

  1. El servidor detecta automáticamente su sistema operativo y encuentra el directorio de registro apropiado

  2. Localiza todos los archivos de registro de MCP y los ordena por hora de modificación (el más nuevo primero)

  3. La página solicitada de archivos de registro se recupera en función de la configuración de paginación

  4. Los archivos se procesan con límites de tamaño para evitar respuestas abrumadoras.

  5. El contenido filtrado se devuelve en un formato estructurado con detalles de paginación.

📄 Licencia

Licencia MIT

Available Tools

1 tool
read_mcp_logsC

Read MCP logs from the standard location

ParametersJSON Schema
NameRequiredDescriptionDefault
customPathNoOptional custom path to log directory (default is system-specific)
fileLimitNoMaximum number of files to read per page (default: 5)
filterNoOptional text to filter log entries by (case-insensitive)
linesNoNumber of lines to read from the end of each log file (default: 100)
pageNoPage number for pagination (default: 1)

TDQS

C2.9/5.0
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 mentions reading logs but fails to describe key behaviors like whether this is a safe read operation, what the output format looks like, or any limitations (e.g., file size constraints, error handling). This leaves significant gaps for a tool with multiple parameters.

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 unnecessary words. It is appropriately sized and front-loaded, 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.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters, no annotations, and no output schema, the description is incomplete. It does not address what the tool returns, how results are structured, or behavioral aspects like pagination details or error conditions, which are crucial for effective 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?

The schema description coverage is 100%, meaning all parameters are documented in the input schema. The description does not add any additional meaning or context beyond what the schema provides, such as explaining interactions between parameters or typical use cases. This meets the baseline for high schema coverage.

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 ('Read') and resource ('MCP logs from the standard location'), providing a specific verb+resource combination. However, with no sibling tools mentioned, it cannot demonstrate differentiation from alternatives, so it falls short of a perfect score.

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 offers no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It simply states what the tool does without context for its application, leaving the agent to infer 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.

  1. 1 tool updatev1.0.0
    • First observedread_mcp_logs
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.1/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools, making disambiguation perfect. The tool's purpose is clearly defined as reading MCP logs from a standard location, leaving no room for confusion with other tools.

Naming Consistency5/5

The single tool name 'read_mcp_logs' follows a clear verb_noun pattern, which is inherently consistent as there are no other tools to compare it against. This naming convention is straightforward and predictable for any potential future tools.

Tool Count2/5

A single tool is too few for a server named 'MCP Log Reader', as it suggests a limited scope that may not cover common log-related operations like filtering, searching, or managing logs. This minimal count feels thin and inadequate for the apparent domain of log reading.

Completeness2/5

The tool surface is severely incomplete for log reading; it only provides a basic read function without essential operations such as filtering by date, searching for specific entries, or handling different log levels. This gap will likely cause agent failures when more complex log interactions are needed.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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