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get_merge_requests

Retrieve merge requests for a GitLab project by ID, with optional state filter and token. Quickly access MRs for review or management.

Instructions

Get merge requests for a GitLab project.

Args:
    project_id: GitLab project ID
    state: MR state (opened, closed, merged, all)
    token: GitLab Personal Access Token (optional)
    ctx: MCP context (automatically injected)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
stateNoopened
tokenNo
ctxNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The get_merge_requests tool handler function. It calls the GitLab API /projects/{id}/merge_requests endpoint with an optional state filter (opened, closed, merged, all), limits results to 10 MRs, and returns formatted output with IID, title, state, and author.
    @mcp.tool()
    async def get_merge_requests(project_id: int, state: str = "opened", token: str = None, ctx=None) -> str:
        """Get merge requests for a GitLab project.
        
        Args:
            project_id: GitLab project ID
            state: MR state (opened, closed, merged, all)
            token: GitLab Personal Access Token (optional)
            ctx: MCP context (automatically injected)
        """
        endpoint = f"/projects/{project_id}/merge_requests?state={state}"
        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 f"No {state} merge requests found."
        
        mrs = []
        for mr in data[:10]:  # Limit to 10 MRs
            mrs.append(f"!{mr['iid']}: {mr['title']} - {mr['state']} ({mr['author']['name']})")
        
        return "\n".join(mrs)
  • The get_merge_requests function is registered as an MCP tool via the @mcp.tool() decorator from FastMCP.
    @mcp.tool()
    async def get_merge_requests(project_id: int, state: str = "opened", token: str = None, ctx=None) -> str:
  • The make_gitlab_request helper function handles all GitLab API calls. It manages token priority (explicit > context headers > env var), constructs the URL with the GitLab base URL, and performs HTTP requests with httpx.
    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 should disclose behavioral traits like pagination, authentication requirements, or read-only nature, but it only lists parameters without such context.

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 docstring format is clear and front-loaded, but mentioning 'ctx' as 'automatically injected' adds unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers parameters but lacks information on prerequisites, behavior for empty results, or pagination; output schema exists but is irrelevant for this score.

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

Parameters5/5

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

The description explains each parameter's meaning (e.g., state: opened, closed, merged, all) beyond the input schema's minimal titles, fully compensating for the 0% 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 'Get merge requests for a GitLab project' which specifies the verb, resource, and context, distinguishing it from sibling tools that fetch other 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?

No guidance is provided on when to use this tool versus alternatives, such as when to filter by state versus using create_merge_request or other related tools.

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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