Git Forensics MCP
Análisis forense de Git MCP
Un servidor especializado del Protocolo de Contexto de Modelo (MCP) para la investigación y el análisis exhaustivos de repositorios Git. Esta herramienta forense proporciona información detallada sobre el historial del repositorio, las relaciones entre ramas y los patrones de desarrollo, centrándose exclusivamente en el análisis de repositorios Git en lugar de en las operaciones generales de GitHub o Git.
Características
El servidor proporciona cuatro herramientas de análisis principales:
Descripción general de la rama (
get_branch_overview)Proporciona una descripción general de alto nivel de los estados y relaciones de las ramas.
Analiza las últimas confirmaciones, los recuentos de confirmaciones y las bases de fusión.
Genera resúmenes estadísticos de las actividades de la sucursal
Análisis del período de tiempo (
analyze_time_period)Analiza la actividad de desarrollo detallada en períodos de tiempo específicos.
Clasifica las confirmaciones (característica, corrección, refactorización, documentación, otras)
Proporciona resúmenes de actividades con patrones de confirmación.
Análisis de cambios de archivos (
analyze_file_changes)Realiza un seguimiento de los cambios en archivos específicos en todas las ramas
Identifica áreas de conflicto potenciales
Proporciona una evaluación de riesgos para las modificaciones de archivos.
Genera un orden de revisión recomendado según los niveles de riesgo
Fusionar recomendaciones (
get_merge_recommendations)Determina estrategias de fusión óptimas
Evalúa los riesgos de conflicto
Identifica puntos críticos del código
Proporciona una guía de fusión paso a paso
Related MCP server: git-intel
Parámetros de entrada
Cada herramienta requiere parámetros específicos:
repoPath: Ruta al repositorio gitbranches: Matriz de nombres de ramas para analizaroutputPath: Ruta donde se escribirán los resultados del análisisParámetros adicionales específicos de la herramienta:
timeRange: Fechas de inicio y finalización del análisis del períodofiles: Matriz de rutas de archivos para el análisis de cambios de archivos
Formato de salida
Todas las herramientas generan archivos JSON que contienen:
Resultados detallados del análisis
Estadísticas resumidas
Evaluaciones de riesgos (cuando corresponda)
Recomendaciones basadas en el análisis
Detalles técnicos
Creado con TypeScript
Utiliza MCP SDK para la implementación del servidor
Ejecuta comandos git a través de procesos secundarios
Proporciona manejo de errores y validación.
Se ejecuta en el transporte stdio
Dependencias
@modelcontextprotocol/sdk
Node.js
Git (debe estar instalado y accesible)
Uso
El servidor funciona como un servicio MCP y se puede integrar con cualquier cliente compatible con MCP. Todos los resultados del análisis se escriben en archivos de salida específicos en formato JSON.
Contribución y licencia
Este proyecto está licenciado bajo la Licencia Apache, versión 2.0 - consulte el archivo LICENSE.txt para obtener más detalles.
Bienvenida la colaboración
Se aceptan bifurcaciones y contribuciones.
Todas las contribuciones se realizarán bajo la Licencia Apache 2.0. Esta licencia permisiva le permite:
Utilice el código comercialmente
Modificar y distribuir el código
Crear obras derivadas
Incluir en otros proyectos
Copyright 2025. Licenciado bajo la Licencia Apache, Versión 2.0; no puede usar este proyecto sin cumplir con la Licencia. Puede obtener una copia de la Licencia en http://www.apache.org/licenses/LICENSE-2.0
Available Tools
4 toolsanalyze_file_changesC
Analyze changes to specific files across branches
| Name | Required | Description | Default |
|---|---|---|---|
| repoPath | Yes | Path to git repository | |
| branches | Yes | Branches to analyze | |
| files | Yes | Files to analyze | |
| outputPath | Yes | Path to write analysis output |
TDQS
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 but only states what the tool does at a high level. It doesn't explain what 'analyze' entails (e.g., type of analysis, output format, whether it writes to disk, performance implications, or error handling), leaving 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.
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's appropriately sized and front-loaded, making it easy to parse quickly.
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 analyzing file changes across branches (a non-trivial operation), no annotations, and no output schema, the description is insufficient. It lacks details on what the analysis produces, how results are formatted, or any behavioral traits, making it incomplete for effective agent use.
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 description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description doesn't add any additional meaning or context about the parameters beyond what's in the schema, resulting in a baseline score of 3.
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 clearly states the action ('analyze changes') and target ('specific files across branches'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'analyze_time_period' or 'get_branch_overview', which might also involve analysis operations.
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?
The description provides no guidance on when to use this tool versus alternatives like 'analyze_time_period' or 'get_branch_overview'. There's no mention of prerequisites, exclusions, or comparative contexts, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
analyze_time_periodC
Analyze detailed development activity in a specific time period
| Name | Required | Description | Default |
|---|---|---|---|
| repoPath | Yes | Path to git repository | |
| branches | Yes | Branches to analyze | |
| timeRange | Yes | ||
| outputPath | Yes | Path to write analysis output |
TDQS
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 'analyzes' activity, implying a read-only operation, but doesn't clarify if it writes output (as suggested by the 'outputPath' parameter), requires specific permissions, has rate limits, or what the analysis entails. This is inadequate for a tool with no 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action and resource, making it easy to parse and understand quickly.
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 no annotations, no output schema, and a tool with 4 parameters (including a nested object), the description is incomplete. It doesn't explain what 'analyze' means in practice, what the output contains, or how it differs from siblings, leaving significant gaps for an agent to use the tool effectively.
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 description coverage is 75% (3 out of 4 parameters have descriptions), so the baseline is 3. The description adds no additional parameter semantics beyond what the schema provides, such as explaining the format of 'timeRange' or the nature of 'outputPath'. It doesn't compensate for the 25% gap in coverage for the nested 'timeRange' object.
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 clearly states the verb 'analyze' and the resource 'detailed development activity in a specific time period', which is specific enough to understand the tool's function. However, it doesn't explicitly differentiate from sibling tools like 'analyze_file_changes' or 'get_branch_overview', which might also analyze development activity but with different scopes or methods.
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?
The description provides no guidance on when to use this tool versus alternatives like 'analyze_file_changes' or 'get_branch_overview'. It mentions analyzing 'detailed development activity' but doesn't specify what that entails or when this tool is preferred over others, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_branch_overviewC
Get high-level overview of branch states and relationships
| Name | Required | Description | Default |
|---|---|---|---|
| repoPath | Yes | Path to git repository | |
| branches | Yes | Branches to analyze | |
| outputPath | Yes | Path to write analysis output |
TDQS
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 mentions 'Get' and 'write analysis output' (via outputPath), implying read and write operations, but doesn't specify if this is safe, requires permissions, or has side effects like file creation. Critical details like error handling or output format are missing, leaving gaps in understanding the tool's behavior.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, making it easy to grasp quickly.
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 a git analysis tool with three parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'high-level overview' entails, how output is formatted, or any behavioral traits like file writing implications. This leaves significant gaps for an AI agent to use the tool effectively.
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 description coverage is 100%, so the schema already documents all three parameters (repoPath, branches, outputPath) with clear descriptions. The description adds no additional meaning beyond the schema, such as explaining relationships between parameters or usage nuances. 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.
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 ('high-level overview of branch states and relationships'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'analyze_file_changes' or 'get_merge_recommendations', which also seem to analyze git repositories but focus on different aspects.
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 versus alternatives. The description lacks context about prerequisites, such as needing a valid git repository, or exclusions, like not handling specific branch states. It doesn't reference sibling tools or suggest scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_merge_recommendationsC
Get detailed merge strategy recommendations
| Name | Required | Description | Default |
|---|---|---|---|
| repoPath | Yes | Path to git repository | |
| branches | Yes | Branches to analyze | |
| outputPath | Yes | Path to write analysis output |
TDQS
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 'Get detailed merge strategy recommendations' but doesn't specify what 'detailed' entails, whether it's read-only or has side effects, if it requires specific permissions, or how it handles errors. For a tool with 3 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.
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 and appropriately sized for its purpose, making it easy to parse quickly.
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 tool has 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'merge strategy recommendations' include, how results are returned or written to outputPath, or any behavioral traits. For a tool that likely involves analysis and output generation, more context is needed.
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 description coverage is 100%, so the input schema fully documents the parameters (repoPath, branches, outputPath). The description doesn't add any meaning beyond the schema, such as explaining how branches are analyzed or what format the output uses. Baseline 3 is appropriate when the schema does the heavy lifting.
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 clearly states the verb 'Get' and the resource 'detailed merge strategy recommendations', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'analyze_file_changes' or 'get_branch_overview', which might also involve repository analysis. The purpose is specific but lacks sibling distinction.
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?
The description provides no guidance on when to use this tool versus alternatives like 'analyze_file_changes' or 'analyze_time_period'. There's no mention of prerequisites, context, or exclusions. It's a basic statement of function without 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.
4 tool updates
- First observed
analyze_file_changes - First observed
analyze_time_period - First observed
get_branch_overview - First observed
get_merge_recommendations
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose with no overlap: analyze_file_changes focuses on file-level changes, analyze_time_period covers time-based activity, get_branch_overview provides branch states, and get_merge_recommendations handles merge strategies. The descriptions make it easy to differentiate between them.
All tools follow a consistent verb_noun pattern (analyze_file_changes, analyze_time_period, get_branch_overview, get_merge_recommendations) with clear, descriptive names. There are no deviations in naming conventions.
With 4 tools, the count is reasonable for a Git forensics server, though it feels slightly minimal. Each tool appears to serve a distinct function, but the scope might benefit from a few more tools for broader coverage without being excessive.
The tools cover analysis and recommendations well, but there are notable gaps for a Git forensics domain, such as missing CRUD operations (e.g., no tools for creating or modifying data) and limited coverage of common forensic tasks like commit history analysis or user activity tracking. Agents might need workarounds for some scenarios.
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