Skip to main content
Glama
AyoubTRD

Git Code Review MCP

by AyoubTRD
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Local

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation4/5

    The tools have distinct purposes: get_diff retrieves diff content, get_file_content provides full file content for context, and get_staged_files lists staged files. While get_diff and get_file_content could be confused for overlapping file content retrieval, the descriptions clarify that get_file_content is for supplemental context when diff is insufficient, maintaining reasonable separation.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with 'get_' prefix: get_diff, get_file_content, get_staged_files. This uniformity makes the tool set predictable and easy to understand, with no deviations in naming style.

    Tool Count3/5

    With only 3 tools, the set feels thin for a code review domain, which typically involves more operations like commenting, approving, or managing reviews. While the tools cover basic retrieval needs, the count is borderline low for the apparent scope, limiting functionality.

    Completeness2/5

    The tool set is severely incomplete for code review workflows. It only provides retrieval operations (get_diff, get_file_content, get_staged_files) but lacks essential actions like creating comments, submitting reviews, or managing pull requests. This creates significant gaps that will cause agent failures in performing full code review tasks.

  • Average 3.3/5 across 3 of 3 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 ISC License.

  • 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 the full burden of behavioral disclosure. It states the action 'retrieve' but lacks details on permissions needed, error handling (e.g., if no staged files exist), output format, or any side effects. This is a significant gap for a tool that interacts with a git repository.

    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 with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose 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?

    Given the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like what the diff output looks like, error conditions, or how it differs from sibling tools, leaving gaps for an AI agent to understand full usage.

    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?

    The input schema has 100% coverage, with one parameter 'repoPath' fully described. The description adds no additional meaning beyond the schema, such as examples or constraints, but the schema's completeness justifies the 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 verb 'retrieve' and the resource 'diff of staged files in a git repository', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_staged_files', which might retrieve similar information without diff details.

    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 'get_staged_files' or 'get_file_content'. There's no mention of prerequisites, such as needing a git repository with staged changes, or any exclusions for usage.

    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 states the tool retrieves a list but doesn't describe the return format (e.g., array of file names, detailed metadata), pagination, error handling, or performance implications. This leaves significant gaps for an agent to understand how the tool behaves beyond its basic function.

    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 with the core action and resource, making it easy to parse quickly. Every part of the sentence earns its place by conveying essential information.

    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 lack of annotations and output schema, the description is incomplete for a tool that retrieves data. It doesn't explain what the returned list contains (e.g., file names, paths, status), how errors are handled, or any limitations (e.g., large repositories). For a read operation with no structured output documentation, this leaves the agent with insufficient context 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?

    The input schema has 100% description coverage, with 'repoPath' clearly documented as 'Full path to the git repository.' The description doesn't add any parameter details beyond this, so it meets the baseline of 3 where the schema does the heavy lifting, but doesn't compensate with additional context like format examples or constraints.

    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 ('list of staged files in a git repository'), making the tool's purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_diff' or 'get_file_content', which might also retrieve git-related information but for different resources.

    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 'get_diff' or 'get_file_content'. It lacks context about scenarios where staged files are needed, prerequisites (e.g., repository must exist), or exclusions (e.g., not for unstaged files).

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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. It mentions the tool retrieves file content, which implies a read-only operation, but doesn't disclose behavioral traits like error handling, performance, or authentication needs. The description adds basic context but lacks depth 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 two sentences with zero waste: the first states the purpose, and the second provides usage guidance. It's front-loaded with essential information and appropriately sized for the tool's complexity.

    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 no annotations and no output schema, the description is complete enough for a simple read operation with clear purpose and usage guidelines. However, it lacks details on return format or error cases, which would be helpful for full contextual 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 already documents both parameters (repoPath and filePath) fully. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or constraints, meeting the baseline for high schema coverage.

    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 ('Retrieve the content') and resource ('a file in a git repository'), distinguishing it from siblings like get_diff (which shows differences) and get_staged_files (which lists staged files). It precisely defines what the tool does.

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

    Usage Guidelines5/5

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

    The description explicitly states when to use this tool: 'Use it when the diff doesn't provide enough context.' This provides clear guidance on usage context and implies an alternative (get_diff), helping the agent choose between siblings effectively.

    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-codereview-mcp MCP server

Copy to your README.md:

Score Badge

git-codereview-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/AyoubTRD/git-codereview-mcp'

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