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create_tag

Create a Git tag on a specified branch or commit. Optionally include an annotation message.

Instructions

Create a new tag.

Args:
    project_id: GitLab project ID
    tag_name: Tag name
    ref: Source branch/commit
    message: Tag message (optional)
    token: GitLab Personal Access Token (optional)
    ctx: MCP context (automatically injected)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
tag_nameYes
refYes
messageNo
tokenNo
ctxNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The 'create_tag' tool handler function. It creates a new GitLab tag by sending a POST request to /projects/{project_id}/repository/tags with tag_name, ref, and optional message.
    @mcp.tool()
    async def create_tag(project_id: int, tag_name: str, ref: str, message: str = "", token: str = None, ctx=None) -> str:
        """Create a new tag.
        
        Args:
            project_id: GitLab project ID
            tag_name: Tag name
            ref: Source branch/commit
            message: Tag message (optional)
            token: GitLab Personal Access Token (optional)
            ctx: MCP context (automatically injected)
        """
        data = {
            "tag_name": tag_name,
            "ref": ref,
            "message": message
        }
        
        result = await make_gitlab_request(f"/projects/{project_id}/repository/tags", "POST", data, ctx=ctx, token=token)
        
        if isinstance(result, dict) and "error" in result:
            return f"Error creating tag: {result['error']}"
        
        return f"Tag created: {result['name']} at {result['commit']['short_id']}"
  • The tool is registered via the @mcp.tool() decorator on line 487.
    @mcp.tool()
    async def create_tag(project_id: int, tag_name: str, ref: str, message: str = "", token: str = None, ctx=None) -> str:
  • The make_gitlab_request helper function is used by create_tag to make the API call to GitLab.
    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?

No annotations are provided, so the description must disclose behavioral traits. It does not mention that the operation is destructive (creates a mutable tag), what happens if the tag name already exists, or authentication requirements. The optional token parameter is noted but its absence's effect is unclear.

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 extremely concise, using a simple bullet list of parameters with brief explanations. Every sentence is essential and directly to the point, with no wasted words.

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 fails to provide context about tag creation nuance (lightweight vs annotated tags), required permissions, error states, or expected outcomes. For a creation tool, additional completeness 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?

With 0% schema description coverage, the description provides one-line explanations for each parameter, adding context beyond titles (e.g., 'GitLab project ID' vs 'Project Id'). However, explanations like 'Source branch/commit' for ref are minimal and lack format guidance. The injection of ctx is clarified. This is adequate but not rich.

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 purpose: 'Create a new tag.' This identifies the verb and resource. It differentiates from siblings like create_branch or delete_tag by focusing on tags, but does not explicitly distinguish from other tag operations or mention the type of tag (lightweight vs annotated).

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_branch or when a tag should be created locally vs via API. The description omits context like prerequisites (e.g., branch existence) or scenarios where this tool is appropriate.

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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