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Qlik Sense MCP Server

get_apps

Retrieve and filter Qlik Sense applications by name, stream, or published status with pagination support for efficient management.

Instructions

Get list of Qlik Sense applications with essential fields and filters (name, stream, published) and pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of apps to return (default: 25, max: 50)
offsetNoNumber of apps to skip for pagination (default: 0)
nameNoWildcard case-insensitive search in application name
streamNoWildcard case-insensitive search in stream name
publishedNoFilter by published status (true/false or 1/0). Default: truetrue

Implementation Reference

  • Core handler function implementing the get_apps tool logic: fetches apps from Qlik Sense Repository API with filtering (name, stream, published), pagination, and returns minimal essential fields.
    def get_comprehensive_apps(self,
                                   limit: int = 25,
                                   offset: int = 0,
                                   name: Optional[str] = None,
                                   stream: Optional[str] = None,
                                   published: Optional[bool] = True) -> Dict[str, Any]:
        """
        Get minimal list of apps with essential fields and proper filtering/pagination.
    
        Returns only: guid, name, description, stream, modified_dttm, reload_dttm.
        Supports case-insensitive wildcard filters for name and stream, and published flag.
        Enforces default limit=25 and maximum limit=50.
        """
        if limit is None or limit < 1:
            limit = 25
        if limit > 50:
            limit = 50
        if offset is None or offset < 0:
            offset = 0
    
        filters: List[str] = []
        if published is not None:
            filters.append(f"published eq {'true' if published else 'false'}")
        if name:
            raw_name = name.replace('*', '')
            safe_name = raw_name.replace("'", "''")
            filters.append(f"name so '{safe_name}'")
        if stream:
            raw_stream = stream.replace('*', '')
            safe_stream = raw_stream.replace("'", "''")
            filters.append(f"stream.name so '{safe_stream}'")
    
        params: Dict[str, Any] = {}
        if filters:
            params["filter"] = " and ".join(filters)
        params["orderby"] = "modifiedDate desc"
    
        apps_result = self._make_request("GET", "app/full", params=params)
    
        if isinstance(apps_result, list):
            apps = apps_result
        elif isinstance(apps_result, dict):
            if "error" in apps_result:
                apps = []
            else:
                apps = apps_result.get("data", []) or apps_result.get("apps", [])
        else:
            apps = []
    
        minimal_apps: List[Dict[str, Any]] = []
        for app in apps:
            try:
                is_published = bool(app.get("published", False))
                stream_name = app.get("stream", {}).get("name", "") if is_published else ""
                minimal_apps.append({
                    "guid": app.get("id", ""),
                    "name": app.get("name", ""),
                    "description": app.get("description") or "",
                    "stream": stream_name or "",
                    "modified_dttm": app.get("modifiedDate", "") or "",
                    "reload_dttm": app.get("lastReloadTime", "") or "",
                })
            except Exception:
                continue
    
        if name:
            lowered = name.lower().replace('*', '')
            minimal_apps = [a for a in minimal_apps if lowered in (a.get("name", "").lower())]
        if stream:
            lowered_stream = stream.lower().replace('*', '')
            minimal_apps = [a for a in minimal_apps if lowered_stream in (a.get("stream", "").lower())]
        if published is not None:
            if published:
                minimal_apps = [a for a in minimal_apps if a.get("stream", "") != ""]
            else:
                minimal_apps = [a for a in minimal_apps if a.get("stream", "") == ""]
    
        total_found = len(minimal_apps)
        paginated_apps = minimal_apps[offset:offset + limit]
    
        return {
            "apps": paginated_apps,
            "pagination": {
                "limit": limit,
                "offset": offset,
                "returned": len(paginated_apps),
                "total_found": total_found,
                "has_more": (offset + limit) < total_found,
                "next_offset": (offset + limit) if (offset + limit) < total_found else None,
            },
        }
  • MCP tool registration and schema definition for get_apps in the list_tools handler.
    Tool(
        name="get_apps",
        description="Get list of Qlik Sense applications with essential fields and filters (name, stream, published) and pagination.",
        inputSchema={
            "type": "object",
            "properties": {
                "limit": {
                    "type": "integer",
                    "description": "Maximum number of apps to return (default: 25, max: 50)",
                    "default": 25
                },
                "offset": {
                    "type": "integer",
                    "description": "Number of apps to skip for pagination (default: 0)",
                    "default": 0
                },
                "name": {
                    "type": "string",
                    "description": "Wildcard case-insensitive search in application name"
                },
                "stream": {
                    "type": "string",
                    "description": "Wildcard case-insensitive search in stream name"
                },
                "published": {
                    "type": "string",
                    "description": "Filter by published status (true/false or 1/0). Default: true",
                    "default": "true"
                }
            }
        }
    ),
  • MCP call_tool dispatcher handler for get_apps: parses arguments, converts types, delegates to repository_api.get_comprehensive_apps, formats JSON response.
    if name == "get_apps":
        limit = arguments.get("limit", 25)
        offset = arguments.get("offset", 0)
        name_filter = arguments.get("name")
        stream_filter = arguments.get("stream")
        published_arg = arguments.get("published", True)
    
        if limit is None or limit < 1:
            limit = 25
        if limit > 50:
            limit = 50
    
        def _to_bool(value: Any, default: bool = True) -> bool:
            if isinstance(value, bool):
                return value
            if isinstance(value, int):
                return value != 0
            if isinstance(value, str):
                v = value.strip().lower()
                if v in ("true", "1", "yes", "y"): return True
                if v in ("false", "0", "no", "n"): return False
            return default
    
        published_bool = _to_bool(published_arg, True)
    
        apps_payload = await asyncio.to_thread(
            self.repository_api.get_comprehensive_apps,
            limit,
            offset,
            name_filter,
            stream_filter,
            published_bool,
        )
        return [
            TextContent(
                type="text",
                text=json.dumps(apps_payload, indent=2, ensure_ascii=False)
            )
        ]
  • Input schema validation for get_apps tool parameters (limit, offset, name, stream, published).
        inputSchema={
            "type": "object",
            "properties": {
                "limit": {
                    "type": "integer",
                    "description": "Maximum number of apps to return (default: 25, max: 50)",
                    "default": 25
                },
                "offset": {
                    "type": "integer",
                    "description": "Number of apps to skip for pagination (default: 0)",
                    "default": 0
                },
                "name": {
                    "type": "string",
                    "description": "Wildcard case-insensitive search in application name"
                },
                "stream": {
                    "type": "string",
                    "description": "Wildcard case-insensitive search in stream name"
                },
                "published": {
                    "type": "string",
                    "description": "Filter by published status (true/false or 1/0). Default: true",
                    "default": "true"
                }
            }
        }
    ),
Behavior3/5

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

With no annotations provided, the description carries the full burden. It mentions pagination behavior and filtering capabilities, which is helpful. However, it doesn't disclose authentication requirements, rate limits, error conditions, or what 'essential fields' specifically includes, leaving gaps in behavioral understanding.

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 a single, well-structured sentence that efficiently conveys the tool's core functionality, key filters, and pagination support. Every element earns its place with no wasted words, making it easy to parse quickly.

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?

For a list tool with 5 parameters and no output schema, the description adequately covers the basic purpose and filtering. However, without annotations or output schema, it should ideally mention more about return format (e.g., what 'essential fields' includes) and any critical constraints to be fully complete.

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 description coverage is 100%, so the schema fully documents all 5 parameters. The description adds minimal value beyond the schema by mentioning filters (name, stream, published) and pagination, but doesn't provide additional context like wildcard syntax examples or interaction effects between parameters.

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 tool's purpose: 'Get list of Qlik Sense applications' with specific resources (applications) and essential fields/filters (name, stream, published). It distinguishes from siblings like get_app_details by focusing on listing rather than detailed retrieval, but doesn't explicitly contrast with other list-like siblings.

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 usage for listing applications with filtering and pagination, suggesting when to use it for bulk retrieval vs. detailed sibling tools. However, it lacks explicit guidance on when to choose this over alternatives like get_app_sheets or get_app_variables for specific needs.

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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