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getDeviceSwitchPorts

Retrieve all switch ports and their configurations for a specific Meraki device by providing its serial number.

Instructions

Get switch ports for a device

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serialYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The MCP tool handler for 'getDeviceSwitchPorts'. It is registered with @mcp.tool() decorator and delegates to call_meraki_method with section='switch' and method='getDeviceSwitchPorts', passing the serial parameter.
    @mcp.tool()
    async def getDeviceSwitchPorts(serial: str) -> str:
        """Get switch ports for a device"""
        return await call_meraki_method("switch", "getDeviceSwitchPorts", serial=serial)
  • The @mcp.tool() decorator on line 485 registers 'getDeviceSwitchPorts' as an MCP tool. It is also listed in the pre_registered_tools array in get_mcp_config() (line 658).
    @mcp.tool()
    async def getDeviceSwitchPorts(serial: str) -> str:
        """Get switch ports for a device"""
        return await call_meraki_method("switch", "getDeviceSwitchPorts", serial=serial)
  • The call_meraki_method async wrapper that call_meraki_method delegates to to_async(_call_meraki_method_internal).
    async def call_meraki_method(section: str, method: str, **params) -> str:
        """Internal async wrapper for pre-registered tools"""
        return await to_async(_call_meraki_method_internal)(section, method, params)
  • The _call_meraki_method_internal function that handles the actual Meraki API call. It validates the section/method, enforces pagination/read-only mode, handles caching, and invokes the meraki dashboard SDK method (dashboard.switch.getDeviceSwitchPorts(serial)).
    def _call_meraki_method_internal(section: str, method: str, params: dict) -> str:
        """Internal helper to call Meraki API methods"""
        pagination_limited = False
        original_params = params.copy()
    
        try:
            # Validate section
            if not hasattr(dashboard, section):
                return json.dumps({
                    "error": f"Invalid section '{section}'",
                    "available_sections": SDK_SECTIONS
                }, indent=2)
    
            section_obj = getattr(dashboard, section)
    
            # Validate method
            if not hasattr(section_obj, method):
                return json.dumps({
                    "error": f"Method '{method}' not found in section '{section}'"
                }, indent=2)
    
            method_func = getattr(section_obj, method)
    
            if not callable(method_func):
                return json.dumps({"error": f"'{method}' is not callable"}, indent=2)
    
            # Determine operation type
            is_read = is_read_only_operation(method)
            is_write = is_write_operation(method)
    
            # Read-only mode check
            if READ_ONLY_MODE and is_write:
                return json.dumps({
                    "error": "Write operation blocked - READ_ONLY_MODE is enabled",
                    "method": method,
                    "hint": "Set READ_ONLY_MODE=false in .env to enable"
                }, indent=2)
    
            # Auto-fill org ID if needed
            sig = inspect.signature(method_func)
            method_params = [p for p in sig.parameters.keys() if p != 'self']
    
            if 'organizationId' in method_params and 'organizationId' not in params and MERAKI_ORG_ID:
                params['organizationId'] = MERAKI_ORG_ID
    
            # Enforce pagination limits
            params_before = params.copy()
            params = enforce_pagination_limits(params, method)
            if params != params_before:
                pagination_limited = True
    
            # Check cache for read operations
            if ENABLE_CACHING and is_read:
                cache_key = create_cache_key(section, method, params)
                cached = cache.get(cache_key)
                if cached is not None:
                    if isinstance(cached, dict):
                        cached['_from_cache'] = True
                    return json.dumps(cached, indent=2)
    
            # Call the method
            result = method_func(**params)
    
            # Invalidate cached read results for this section after any write operation
            if ENABLE_CACHING and is_write:
                cache.invalidate(section)
    
            # Check response size and handle large responses
            result_json = json.dumps(result)
            estimated_tokens = estimate_token_count(result_json)
    
            if ENABLE_FILE_CACHING and estimated_tokens > MAX_RESPONSE_TOKENS:
                # Save full response to file
                filepath = save_response_to_file(result, section, method, original_params)
    
                # Create truncated response with metadata
                truncated_response = create_truncated_response(result, filepath, section, method, original_params)
    
                # Add pagination warning if limits were enforced
                if pagination_limited:
                    truncated_response["_pagination_limited"] = True
                    truncated_response["_pagination_message"] = f"Request modified: pagination limited to {MAX_PER_PAGE} items per page"
    
                # Cache the truncated response (not the full result)
                if ENABLE_CACHING and is_read:
                    cache_key = create_cache_key(section, method, params)
                    cache.set(cache_key, truncated_response)
    
                return json.dumps(truncated_response, indent=2)
    
            # Normal response (small enough)
            response_data = result
            if pagination_limited and isinstance(response_data, dict):
                response_data["_pagination_limited"] = True
                response_data["_pagination_message"] = f"Request modified: pagination limited to {MAX_PER_PAGE} items per page"
    
            # Cache read results
            if ENABLE_CACHING and is_read:
                cache_key = create_cache_key(section, method, params)
                cache.set(cache_key, response_data)
    
            return json.dumps(response_data, indent=2)
    
        except meraki.exceptions.APIError as e:
            return json.dumps({
                "error": "Meraki API Error",
                "message": str(e),
                "status": getattr(e, 'status', 'unknown')
            }, indent=2)
        except TypeError as e:
            return json.dumps({
                "error": "Invalid parameters",
                "message": str(e),
                "hint": f"Use get_method_info(section='{section}', method='{method}') for parameter details"
            }, indent=2)
        except Exception as e:
            return json.dumps({
                "error": str(e),
                "type": type(e).__name__
            }, indent=2)
  • The input schema for getDeviceSwitchPorts: requires a single 'serial' parameter of type str. The return type is str (JSON-encoded result).
    async def getDeviceSwitchPorts(serial: str) -> str:
        """Get switch ports for a device"""
        return await call_meraki_method("switch", "getDeviceSwitchPorts", serial=serial)
Behavior2/5

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

No annotations provided, and the description only says 'Get switch ports', implying it is read-only but provides no additional behavioral context such as required permissions, rate limits, or pagination.

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 a single short sentence, which is concise. However, it is too minimal; a slightly more informative description would be appropriate given the context.

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 no annotations and 0% schema coverage, the description lacks completeness. It does not specify what the output contains (list of ports with fields), nor does it mention important behavioral aspects for a tool with an output schema.

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?

Schema coverage is 0% and the description does not explain the 'serial' parameter. The parameter name 'serial' hints at a device serial number, but the description adds no explanatory value beyond the schema.

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 states the action 'Get' and resource 'switch ports' clearly. It indicates read operation but does not differentiate from sibling tools like 'updateDeviceSwitchPort' or 'getDevice', which limits differentiation.

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

Usage Guidelines1/5

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

No guidance on when to use this tool versus alternatives, no prerequisites or conditions for use, and no mention of limitations.

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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