Skip to main content
Glama

delete_branch

Delete a branch from a GitLab project by providing the project ID and branch name to clean up repositories.

Instructions

Delete a branch.

Args:
    project_id: GitLab project ID
    branch_name: Branch name to delete
    token: GitLab Personal Access Token (optional)
    ctx: MCP context (automatically injected)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
branch_nameYes
tokenNo
ctxNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The 'delete_branch' tool handler function. It is registered as an MCP tool via @mcp.tool() decorator, accepts project_id and branch_name parameters, URL-encodes the branch name, and sends a DELETE request to the GitLab API endpoint /projects/{project_id}/repository/branches/{encoded_branch}. Returns a success message or error.
    @mcp.tool()
    async def delete_branch(project_id: int, branch_name: str, token: str = None, ctx=None) -> str:
        """Delete a branch.
        
        Args:
            project_id: GitLab project ID
            branch_name: Branch name to delete
            token: GitLab Personal Access Token (optional)
            ctx: MCP context (automatically injected)
        """
        import urllib.parse
        encoded_branch = urllib.parse.quote(branch_name, safe='')
        result = await make_gitlab_request(f"/projects/{project_id}/repository/branches/{encoded_branch}", "DELETE", ctx=ctx, token=token)
        
        if isinstance(result, dict) and "error" in result:
            return f"Error deleting branch: {result['error']}"
        
        return f"Branch '{branch_name}' deleted successfully"
  • The tool is registered using the @mcp.tool() decorator on the delete_branch function. The FastMCP instance 'mcp' is created at line 9.
    @mcp.tool()
  • The make_gitlab_request helper function used by delete_branch to execute HTTP requests to the GitLab API. delete_branch calls it with method='DELETE'.
    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?

The description does not disclose any behavioral traits beyond the fact that it deletes a branch. It does not mention irreversibility, required permissions, or side effects (e.g., impact on merge requests). With no annotations provided, the description carries the full burden, and it falls short.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise at two lines covering purpose and parameters. It is front-loaded with the action. However, the use of a Python docstring-style block (Args:) is not standard for MCP descriptions and may be less readable for an AI agent.

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 destructive nature of the tool, the description is incomplete. It does not explain return values (though an output schema exists), error cases, or idempotency. An agent cannot determine if deleting a non-existent branch fails or succeeds silently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description lists parameters with one-line explanations (e.g., 'GitLab Personal Access Token (optional)'), adding slight value over the schema's 0% coverage. However, the required parameters 'project_id' and 'branch_name' are not explained beyond their variable names, leaving ambiguity about format 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 ('Delete a branch') and the resource ('branch'). It distinguishes from sibling tools like 'create_branch' or 'compare_branches' by explicitly naming the delete operation. However, it lacks specificity about the GitLab context, though the 'project_id' parameter implies it.

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 (e.g., deleting a tag or project). There is no mention of prerequisites, such as the branch not being the default or having no active merge requests. The description assumes the agent knows when deletion is appropriate.

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

Install Server

Other Tools

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/skmprb/gitlab-clone-mcp-server'

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