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update_file

Update file content in a GitLab repository by specifying project ID, file path, new content, branch, and commit message.

Instructions

Update an existing file in repository.

Args:
    project_id: GitLab project ID
    file_path: Path to the file
    content: New file content
    branch: Target branch
    commit_message: Commit message
    token: GitLab Personal Access Token (optional)
    ctx: MCP context (automatically injected)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
file_pathYes
contentYes
branchYes
commit_messageYes
tokenNo
ctxNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'update_file' tool. It updates an existing file in a GitLab repository by making a PUT request to the repository files API endpoint with the file path, content, branch, and commit message.
    @mcp.tool()
    async def update_file(project_id: int, file_path: str, content: str, branch: str, commit_message: str, token: str = None, ctx=None) -> str:
        """Update an existing file in repository.
        
        Args:
            project_id: GitLab project ID
            file_path: Path to the file
            content: New file content
            branch: Target branch
            commit_message: Commit message
            token: GitLab Personal Access Token (optional)
            ctx: MCP context (automatically injected)
        """
        import urllib.parse
        encoded_path = urllib.parse.quote(file_path, safe='')
        data = {
            "branch": branch,
            "content": content,
            "commit_message": commit_message
        }
        
        result = await make_gitlab_request(f"/projects/{project_id}/repository/files/{encoded_path}", "PUT", data, ctx=ctx, token=token)
        
        if isinstance(result, dict) and "error" in result:
            return f"Error updating file: {result['error']}"
        
        return f"File updated: {file_path} in branch {branch}"
  • The tool is registered via the @mcp.tool() decorator on the update_file async function, using FastMCP's automatic tool registration mechanism.
    @mcp.tool()
    async def update_file(project_id: int, file_path: str, content: str, branch: str, commit_message: str, token: str = None, ctx=None) -> str:
  • Helper function used by update_file to make the actual HTTP PUT request to the GitLab API.
    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, and the description only indicates mutation ('Update'). It does not disclose side effects, permission requirements, rate limits, or any behavioral traits beyond the basic operation.

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

Conciseness3/5

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

The description is reasonably concise with an args section, but includes a boilerplate line about ctx injection that adds little value. It is adequately structured but could be more concise.

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?

The description does not cover return values despite an output schema being present. It lacks important context like file existence requirements, branch validity, and error scenarios, making it incomplete for a mutation tool.

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 minimal explanations (e.g., 'project_id: GitLab project ID'), which adds some value over the schema (0% coverage). However, it does not elaborate on formatting, constraints, or usage beyond the parameter names.

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 action ('Update') and the resource ('an existing file in repository'). It effectively distinguishes from sibling tools like create_file, delete_file, and get_file_content.

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

Usage Guidelines3/5

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

The description implies the file must exist ('existing file') but does not explicitly state when to use this tool over alternatives like create_file. No guidance on prerequisites or context.

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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