Git Forensics MCP
Git 取证 MCP
专用于深度 git 存储库调查和分析的模型上下文协议 (MCP) 服务器。此取证工具提供对存储库历史记录、分支关系和开发模式的详细洞察,专注于 git 存储库分析,而非常规的 GitHub 或 git 操作。
特征
该服务器提供四种主要分析工具:
分支概览(
get_branch_overview)提供分支状态和关系的高级概述
分析最后的提交、提交计数和合并基础
生成分支机构活动的统计摘要
时间段分析(
analyze_time_period)分析特定时间段内的详细开发活动
对提交进行分类(功能、修复、重构、文档、其他)
提供带有提交模式的活动摘要
文件更改分析(
analyze_file_changes)跟踪跨分支的特定文件的更改
确定潜在冲突区域
提供文件修改的风险评估
根据风险等级生成建议的审核顺序
合并建议(
get_merge_recommendations)确定最佳合并策略
评估冲突风险
识别代码热点
提供分步合并指导
Related MCP server: git-intel
输入参数
每个工具都需要特定的参数:
repoPath:git 存储库的路径branches:要分析的分支名称数组outputPath:分析结果写入的路径其他特定于工具的参数:
timeRange:周期分析的开始和结束日期files:用于文件更改分析的文件路径数组
输出格式
所有工具输出的 JSON 文件均包含以下内容:
详细分析结果
汇总统计数据
风险评估(如适用)
基于分析的建议
技术细节
使用 TypeScript 构建
使用 MCP SDK 实现服务器
通过子进程执行 git 命令
提供错误处理和验证
在 stdio 传输上运行
依赖项
@modelcontextprotocol/sdk
Node.js
Git(必须安装并可访问)
用法
该服务器作为 MCP 服务运行,可与任何兼容 MCP 的客户端集成。所有分析结果均以 JSON 格式写入指定的输出文件。
贡献和许可
该项目根据 Apache 许可证 2.0 版获得许可 - 有关详细信息,请参阅LICENSE.txt文件。
欢迎合作
欢迎分叉和贡献。
所有贡献均遵循 Apache 2.0 许可证。此许可证允许您:
将代码用于商业用途
修改和分发代码
创作衍生作品
包含在其他项目中
版权所有 2025。本项目遵循 Apache 许可证 2.0 版;除非遵守该许可证,否则您不得使用本项目。您可以在http://www.apache.org/licenses/LICENSE-2.0获取该许可证的副本。
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. Dates show when Glama detected each change.
4 tool updates
- First observed
analyze_file_changes - First observed
analyze_time_period - First observed
get_branch_overview - First observed
get_merge_recommendations
TDQS
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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