Skip to main content
Glama
deenesjakoruzh
lex-tools

@lex-tools/codebase-context-dumper

Official
by lex-tools
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Local

Servidor MCP de volcador de contexto de código base

versión npm Licencia: Apache-2.0

Un servidor de Protocolo de Contexto de Modelo (MCP) diseñado para volcar fácilmente el contexto de su base de código en Modelos de Lenguaje Grandes (LLM).

¿Por qué usar esto?

Las ventanas de contexto grandes en los LLM son potentes, pero seleccionar y formatear manualmente archivos de una base de código extensa resulta tedioso. Esta herramienta automatiza el proceso mediante:

  • Escaneando recursivamente el directorio de su proyecto.

  • Incluye archivos de texto del árbol de directorios especificado que no estén excluidos por las reglas .gitignore .

  • Omitir automáticamente archivos binarios.

  • Concatenar el contenido con marcadores de ruta de archivo claros.

  • Admite fragmentación para gestionar bases de código más grandes que la ventana de contexto de LLM.

  • Integración perfecta con clientes compatibles con MCP.

Related MCP server: code-index-mcp

Uso (recomendado: npx)

La forma más sencilla de utilizar esta herramienta es a través de npx , que ejecuta la última versión sin necesidad de una instalación local.

Configure su cliente MCP (por ejemplo, Claude Desktop, extensiones de VS Code) para usar el siguiente comando:

{
  "mcpServers": {
    "codebase-context-dumper": {
      "command": "npx",
      "args": [
        "-y",
        "@lex-tools/codebase-context-dumper"
      ]
    }
  }
}

El cliente MCP podrá entonces invocar la herramienta dump_codebase_context proporcionada por este servidor.

Características y detalles de la herramienta

Herramienta: dump_codebase_context

Lee recursivamente archivos de texto de un directorio específico, respetando las reglas de .gitignore y omitiendo archivos binarios. Concatena el contenido con los encabezados y pies de página de las rutas de archivo. Permite fragmentar la salida para bases de código extensas.

Funcionalidad :

  • Escanea el directorio proporcionado en base_path .

  • Respeta los archivos .gitignore en todos los niveles (incluidos los anidados y .git por defecto).

  • Detecta y omite archivos binarios.

  • Lee el contenido de cada archivo de texto válido.

  • Antepone un encabezado ( --- START: relative/path/to/file --- ) y añade un pie de página ( --- END: relative/path/to/file --- ) al contenido de cada archivo.

  • Concatena todo el contenido del archivo procesado en una sola cadena.

Parámetros de entrada :

  • base_path (cadena, obligatoria): la ruta absoluta al directorio del proyecto a escanear.

  • num_chunks (entero, opcional, valor predeterminado: 1): El número total de fragmentos en los que se dividirá la salida. Debe ser >= 1.

  • chunk_index (entero, opcional, valor predeterminado: 1): El índice basado en 1 del fragmento que se va a devolver. Requiere que num_chunks > 1 y chunk_index <= num_chunks .

Salida : Devuelve el contenido de texto concatenado (y potencialmente fragmentado).

Instalación y uso local (avanzado)

Si prefiere ejecutar una versión local (por ejemplo, para desarrollo):

  1. Clonar el repositorio:

    git clone git@github.com:lex-tools/codebase-context-dumper.git
cd codebase-context-dumper

  2. Instalar dependencias:

    npm install

  3. Construir el servidor:

    npm run build

  4. Configure su cliente MCP para que apunte a la salida de compilación local:

    {
  "mcpServers": {
    "codebase-context-dumper": {
      "command": "/path/to/your/local/codebase-context-dumper/build/index.js" // Adjust path
    }
  }
}

Contribuyendo

¡Agradecemos sus contribuciones! Consulte CONTRIBUTING.md para obtener más información sobre el desarrollo, la depuración y el lanzamiento de nuevas versiones.

Licencia

Este proyecto está licenciado bajo la Licencia Apache 2.0. Consulte el archivo de LICENCIA para más detalles.

Available Tools

1 tool
dump_codebase_contextA

Recursively reads text files from a specified directory, respecting .gitignore rules and skipping binary files. Concatenates content with file path headers/footers. Supports chunking the output for large codebases.

ParametersJSON Schema
NameRequiredDescriptionDefault
base_pathYesThe absolute path to the project directory to scan.
num_chunksNoOptional total number of chunks to divide the output into (default: 1).
chunk_indexNoOptional 1-based index of the chunk to return (default: 1). Requires num_chunks > 1.

TDQS

A4/5.0
Behavior4/5

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 effectively describes key operational traits: recursive file reading, .gitignore respect, binary file skipping, output formatting with headers/footers, and chunking for large outputs. However, it doesn't mention potential limitations like file size constraints, permission requirements, or error handling, leaving some gaps.

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 highly concise and well-structured in two sentences: the first covers core functionality and constraints, the second addresses scalability. Every phrase adds value (e.g., 'respecting .gitignore rules', 'skipping binary files', 'chunking the output'), with no wasted words or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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

Given the tool's moderate complexity (recursive file operations, chunking) and lack of annotations/output schema, the description does a good job covering core behavior and constraints. It explains what the tool does, key features, and output handling, but omits details like return format, error scenarios, or performance implications, which would enhance completeness for an agent.

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?

Schema description coverage is 100%, so the input schema already fully documents all three parameters (base_path, num_chunks, chunk_index). The description adds no additional parameter-specific information beyond what's in the schema, such as examples or edge cases. The baseline score of 3 reflects adequate but minimal value addition from the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('recursively reads text files', 'concatenates content with file path headers/footers') and resource ('from a specified directory'), including key behavioral details like respecting .gitignore rules and skipping binary files. With no sibling tools, it fully defines the tool's unique purpose without redundancy.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for scanning codebases ('large codebases') and mentions chunking for scalability, but provides no explicit guidance on when to use this tool versus alternatives or any prerequisites. Since there are no sibling tools, the lack of comparative guidance is less critical, but still leaves usage context somewhat open-ended.

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. 1 tool update
    • First observeddump_codebase_context
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A3.9/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool has a single, clearly defined purpose.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against for patterns or conventions.

Tool Count2/5

One tool is too few for most practical server purposes, as it severely limits functionality and interaction. While the tool is well-described, a single tool feels thin and incomplete for a codebase context server.

Completeness2/5

The server's purpose appears to be codebase context management, but with only a dump tool, there are significant gaps. Missing operations like search, filter, update, or delete context make the surface incomplete and likely insufficient for agent workflows.

Maintenance

ActivityInactive
ResponsivenessSyncing

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

Related MCP Servers

Appeared in Searches

Latest Blog Posts

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/lex-tools/codebase-context-dumper'

If you have feedback or need assistance with the MCP directory API, please join our Discord server