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Código base MCP

Una implementación de servidor de Protocolo de contexto de modelo (MCP) que proporciona herramientas para recuperar y analizar bases de código completas utilizando RepoMix .

Este MCP permite que los agentes de IA como Composer Agent de Cursor lean y comprendan automáticamente bases de código completas a la vez, lo que hace más fácil para los desarrolladores trabajar con bases de código grandes y para los asistentes de IA tener un contexto completo de un proyecto.

Características

  • 📚 Recuperación de código base : recupera todo el código base como una única salida de texto en diferentes formatos (XML, Markdown, Plain)

  • 🌐 Compatibilidad con repositorios remotos : procese repositorios remotos de GitHub directamente

  • 💾 Guardado de archivo : guarda el código base procesado en un archivo

  • 🔧 Opciones personalizables : controla cómo se procesa el código base con varias opciones (comentarios, números de línea, resúmenes de archivos, etc.)

Related MCP server: CodeAlive MCP

Instalación

De NPM (Recomendado)

# Install the package globally
npm install -g codebase-mcp

# Install RepoMix (required dependency)
codebase-mcp install

Desde GitHub

# Clone the repository
git clone https://github.com/DeDeveloper23/codebase-mcp.git

# Navigate to the project directory
cd codebase-mcp

# Install dependencies
npm install

# Build the project
npm run build

# Install globally
npm install -g .

# Install RepoMix (required dependency)
codebase-mcp install

Integración con Cursor

Para utilizar este MCP con el Agente Composer de Cursor:

  1. Abrir cursor IDE

  2. Haga clic en el icono del Compositor en la barra lateral.

  3. Haga clic en el botón "Servidores MCP" en la parte superior

  4. Haga clic en "Agregar nuevo servidor MCP"

  5. Complete los datos:

    • Nombre: Codebase MCP (o cualquier nombre que prefieras)

    • Tipo: command

    • Comando: codebase-mcp start

  6. Haga clic en "Agregar" para guardar

Una vez agregado, el MCP proporcionará tres herramientas poderosas al Composer Agent:

Herramientas disponibles

  1. obtenerCódigobase

    • Propósito: Analiza su espacio de trabajo/proyecto actual

    • Úselo cuando: desee que la IA comprenda todo su código base

    • Ejemplo de mensaje: "Analice mi código base para comprender su estructura".

  2. obtener base de código remoto

    • Propósito: obtiene y analiza cualquier repositorio público de GitHub

    • Úselo cuando: desee explorar o comprender otros proyectos

    • Ejemplo de solicitud: "¿Puedes analizar el repositorio en github.com/username/repo?"

  3. guardar código base

    • Propósito: Guarda el análisis del código base en un archivo para su uso posterior

    • Úselo cuando: desee conservar la instantánea del código base o compartirla

    • Ejemplo de mensaje: "Guardar un análisis de este código base para revisarlo más tarde"

Ejemplo de uso en Cursor

A continuación se muestran algunos ejemplos de indicaciones que puede utilizar con Composer Agent:

"Analyze my current project and explain its main components."

"Can you look at the tensorflow/tensorflow repository and explain how their testing framework works?"

"Save an analysis of my project to 'codebase-analysis.md' in markdown format."

El agente Composer utilizará automáticamente la herramienta adecuada en función de su solicitud.

Uso fuera del cursor

Iniciando el servidor MCP

codebase-mcp start

Esto iniciará el servidor MCP en modo stdio, que puede ser utilizado por cualquier cliente compatible con MCP.

Licencia

Instituto Tecnológico de Massachusetts (MIT)

Available Tools

3 tools
getCodebaseC

Retrieve the entire codebase as a single text output using RepoMix

ParametersJSON Schema
NameRequiredDescriptionDefault
cwdNoCurrent working directory of the codebase (defaults to current dir)
formatNoOutput format (xml, markdown, or plain)xml
ignorePatternsNoIgnore patterns (using glob patterns, comma-separated)
includeDirectoryStructureNoInclude directory structure
includeFileSummaryNoInclude summary of each file
includePatternsNoInclude patterns (using glob patterns, comma-separated)
removeCommentsNoRemove comments from the code
removeEmptyLinesNoRemove empty lines from the code
showLineNumbersNoShow line numbers

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but only states it retrieves code as text. It lacks critical behavioral details: whether this is a read-only operation, potential performance impacts for large codebases, authentication needs, or output format specifics beyond 'single text output'.

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?

Single sentence, front-loaded with core purpose, zero wasted words. It efficiently conveys the essential action without unnecessary elaboration.

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?

For a complex tool with 9 parameters and no annotations or output schema, the description is inadequate. It doesn't explain the output structure, performance considerations, or error handling, leaving significant gaps for agent understanding.

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 schema fully documents all 9 parameters. The description adds no parameter-specific information beyond implying retrieval scope ('entire codebase'), maintaining the baseline score 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 verb ('Retrieve') and resource ('entire codebase'), specifying it outputs as 'single text output using RepoMix'. It distinguishes from 'saveCodebase' (write vs. read) but not explicitly from 'getRemoteCodebase' (local vs. remote retrieval).

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 on when to use this tool versus alternatives. It doesn't mention 'getRemoteCodebase' for remote codebases or 'saveCodebase' for saving output, leaving the agent to infer usage from tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

getRemoteCodebaseC

Retrieve a remote repository's codebase as a single text output using RepoMix

ParametersJSON Schema
NameRequiredDescriptionDefault
formatNoOutput format (xml, markdown, or plain)xml
ignorePatternsNoIgnore patterns (using glob patterns, comma-separated)
includeDirectoryStructureNoInclude directory structure
includeFileSummaryNoInclude summary of each file
includePatternsNoInclude patterns (using glob patterns, comma-separated)
removeCommentsNoRemove comments from the code
removeEmptyLinesNoRemove empty lines from the code
repoYesGitHub repository URL or shorthand format (e.g., 'username/repo')
showLineNumbersNoShow line numbers

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but lacks critical behavioral details. It mentions output is 'a single text output' but doesn't disclose size limits, rate limits, authentication needs, error handling, or what 'RepoMix' entails. For a tool with 9 parameters and no annotations, this is insufficient.

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 front-loads the core purpose without wasted words. Every part earns its place by specifying retrieval, resource, output format, and method.

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?

For a complex tool with 9 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain the return structure, potential errors, or behavioral constraints, leaving significant gaps for the agent to operate effectively.

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 parameters are well-documented in the schema. The description adds no additional parameter semantics beyond implying the tool handles remote repositories via 'repo', which aligns with the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 ('Retrieve') and resource ('remote repository's codebase'), specifying it returns 'a single text output using RepoMix'. It distinguishes from sibling 'getCodebase' by emphasizing 'remote' and 'RepoMix', but doesn't explicitly contrast with 'saveCodebase'.

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 explicit guidance on when to use this tool versus siblings 'getCodebase' or 'saveCodebase'. The description implies usage for remote repositories but doesn't specify alternatives or exclusions, leaving the agent to infer context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

saveCodebaseC

Save the codebase to a file using RepoMix

ParametersJSON Schema
NameRequiredDescriptionDefault
cwdNoCurrent working directory of the codebase (defaults to current dir)
formatNoOutput format (xml, markdown, or plain)xml
ignorePatternsNoIgnore patterns (using glob patterns, comma-separated)
includeDirectoryStructureNoInclude directory structure
includeFileSummaryNoInclude summary of each file
includePatternsNoInclude patterns (using glob patterns, comma-separated)
outputFileNoOutput file pathrepomix-output.txt
removeCommentsNoRemove comments from the code
removeEmptyLinesNoRemove empty lines from the code
showLineNumbersNoShow line numbers

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 full burden for behavioral disclosure. It states 'Save' which implies a write operation, but doesn't specify file system permissions, whether it overwrites existing files, error handling, or output format details. The mention of 'RepoMix' adds some context but lacks operational specifics needed for a mutation tool.

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 gets straight to the point. It uses minimal words to convey the core functionality without any fluff or redundant information. Every word earns its place.

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?

For a mutation tool with 10 parameters and no annotations or output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, or important behavioral aspects like file overwriting. The high parameter count and mutation nature require more contextual information than provided.

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%, providing comprehensive parameter documentation. The description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in description.

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 ('Save') and resource ('codebase to a file') with the specific tool 'RepoMix'. It distinguishes from sibling tools 'getCodebase' and 'getRemoteCodebase' by indicating a save/write operation rather than retrieval. However, it doesn't specify what exactly gets saved (e.g., entire codebase, filtered content).

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 about when to use this tool versus alternatives. The description doesn't mention sibling tools or any contextual cues for choosing this over 'getCodebase' or 'getRemoteCodebase'. It's a standalone statement with no usage context.

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. 3 tool updatesv1.0.0
    • First observedgetCodebase
    • First observedgetRemoteCodebase
    • First observedsaveCodebase

TDQS

B3.1/5.0
Disambiguation4/5

The three tools have distinct purposes: retrieving local codebase, retrieving remote codebase, and saving codebase. While 'getCodebase' and 'getRemoteCodebase' both retrieve code, the local/remote distinction is clear. There's minor potential confusion about whether 'saveCodebase' saves the local or remote version, but overall boundaries are well-defined.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with camelCase styling: getCodebase, getRemoteCodebase, saveCodebase. The naming is predictable and follows the same grammatical structure throughout, making it easy for agents to understand the action-object relationship.

Tool Count3/5

With only 3 tools, this feels quite minimal for a 'Codebase MCP' server. While the tools cover basic retrieval and saving operations, the scope seems limited - there are no tools for searching, analyzing, modifying, or managing codebase components. The count is borderline thin for what could be expected from a codebase management system.

Completeness2/5

For a codebase management server, there are significant gaps in functionality. The tools only provide retrieval and saving operations using RepoMix, but lack any tools for code analysis, search, modification, version control operations, or component management. This creates a dead-end surface where agents can only get and save entire codebases without any ability to work with code meaningfully.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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