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get_commits

Retrieve recent commits from a GitLab project by providing the project ID and optional branch name.

Instructions

Get recent commits for a project.

Args:
    project_id: GitLab project ID
    ref_name: Branch name (default: main)
    token: GitLab Personal Access Token (optional)
    ctx: MCP context (automatically injected)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
ref_nameNomain
tokenNo
ctxNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The get_commits tool handler: fetches recent commits from the GitLab API, formats them with short_id, title (truncated to 60 chars), and author name. Returns up to 10 commits.
    @mcp.tool()
    async def get_commits(project_id: int, ref_name: str = "main", token: str = None, ctx=None) -> str:
        """Get recent commits for a project.
        
        Args:
            project_id: GitLab project ID
            ref_name: Branch name (default: main)
            token: GitLab Personal Access Token (optional)
            ctx: MCP context (automatically injected)
        """
        endpoint = f"/projects/{project_id}/repository/commits?ref_name={ref_name}"
        data = await make_gitlab_request(endpoint, ctx=ctx, token=token)
        
        if isinstance(data, dict) and "error" in data:
            return f"Error: {data['error']}"
        if not data:
            return "No commits found."
        
        commits = []
        for commit in data[:10]:
            short_id = commit['short_id']
            title = commit['title'][:60] + ('...' if len(commit['title']) > 60 else '')
            author = commit['author_name']
            commits.append(f"• {short_id}: {title} ({author})")
        return "\n".join(commits)
  • The tool is registered using the @mcp.tool() decorator on the get_commits async function, which registers it with FastMCP under the name 'get_commits'.
    @mcp.tool()
  • The function signature and docstring define the schema: project_id (int, required), ref_name (str, default 'main'), token (optional), and ctx (injected context).
    async def get_commits(project_id: int, ref_name: str = "main", token: str = None, ctx=None) -> str:
        """Get recent commits for a project.
        
        Args:
            project_id: GitLab project ID
            ref_name: Branch name (default: main)
            token: GitLab Personal Access Token (optional)
            ctx: MCP context (automatically injected)
        """
  • The make_gitlab_request helper function used by get_commits to make HTTP requests to the GitLab API with token resolution from explicit param, request context headers, or environment variable.
    async def make_gitlab_request(endpoint: str, method: str = "GET", data: dict = None, ctx=None, token: str = None) -> dict[str, Any] | None:
        """Make a request to GitLab API with proper error handling."""
        # Priority: 1. Explicit token parameter, 2. Context headers, 3. Environment variable
        
        # If no explicit token provided, try to get from context
        if not token and ctx and hasattr(ctx, 'request_context') and ctx.request_context:
            # Try to get from request headers
            if hasattr(ctx.request_context, 'headers'):
                token = ctx.request_context.headers.get('GITLAB_TOKEN')
        
        # Fallback to environment variable
        if not token:
            token = os.getenv("GITLAB_TOKEN")
        
        if not token:
            return {"error": "GitLab token not provided. Please provide a token parameter, GITLAB_TOKEN in the request headers, or set the environment variable."}
        
        # Get GitLab URL (from context or environment)
        gitlab_url = os.getenv("GITLAB_URL", "https://gitlab.com")
        
        headers = {
            "PRIVATE-TOKEN": token,
            "Content-Type": "application/json"
        }
        
        url = f"{gitlab_url}/api/v4{endpoint}"
        
        async with httpx.AsyncClient() as client:
            try:
                if method == "GET":
                    response = await client.get(url, headers=headers, timeout=30.0)
                elif method == "POST":
                    response = await client.post(url, headers=headers, json=data, timeout=30.0)
                elif method == "PUT":
                    response = await client.put(url, headers=headers, json=data, timeout=30.0)
                elif method == "DELETE":
                    response = await client.delete(url, headers=headers, timeout=30.0)
                
                response.raise_for_status()
                return response.json() if response.content else {"success": True}
            except Exception as e:
                return {"error": str(e)}
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It only says 'get recent commits', implying a read operation, but does not define 'recent', mention pagination, rate limits, or any constraints. The auto-injected context is noted, but overall behavioral detail is sparse.

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 short and efficiently structured, with a purpose sentence followed by a bullet-point argument list. Every sentence contributes information, and there is no redundancy.

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?

Despite having an output schema, the description does not clarify what constitutes 'recent' or what the return format looks like. It lacks details on error cases, scope (e.g., only one ref), and does not leverage the output schema to reduce the burden. For a tool with multiple parameters and an output schema, completeness is insufficient.

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 coverage is 0%, so the description must compensate. It adds meaning: project_id is a GitLab ID, ref_name is branch name, token is optional, ctx is auto-injected. This adds value beyond the schema types and defaults, but is minimal and partly repeats schema information.

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 'commits for a project', making the purpose unambiguous. However, it does not differentiate from related sibling tools like 'get_repository_files' or 'compare_branches', which also read data.

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 such as 'create_commit' or 'cherry_pick_commit'. The description only explains its basic function without context for selection.

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

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