Skip to main content
Glama
davidorex

Git Forensics MCP

by davidorex

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    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.

    Naming Consistency5/5

    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.

    Tool Count4/5

    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.

    Completeness3/5

    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.

  • Average 2.9/5 across 4 of 4 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • 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 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.

    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'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.

    Completeness2/5

    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.

    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 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.

    Purpose4/5

    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.

    Usage Guidelines2/5

    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.

  • Behavior2/5

    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.

    Conciseness5/5

    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.

    Completeness2/5

    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.

    Parameters3/5

    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.

    Purpose4/5

    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.

    Usage Guidelines2/5

    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.

  • Behavior2/5

    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.

    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'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.

    Completeness2/5

    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.

    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 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.

    Purpose4/5

    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.

    Usage Guidelines2/5

    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.

  • 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 '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.

    Conciseness5/5

    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.

    Completeness2/5

    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.

    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 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.

    Purpose4/5

    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.

    Usage Guidelines2/5

    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.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

git-forensics-mcp MCP server

Copy to your README.md:

Score Badge

git-forensics-mcp MCP server

Copy to your README.md:

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/davidorex/git-forensics-mcp'

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