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michaelkrasa

Alpha ESS MCP Server

by michaelkrasa

authenticate_alphaess

Validate credentials for Alpha ESS solar inverter and battery system API access to enable energy monitoring and configuration.

Instructions

Authenticate with the Alpha ESS Open API to validate credentials.

Returns:
    dict: Authentication result with success status and message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • main.py:310-357 (handler)
    The main handler function for the 'authenticate_alphaess' tool, decorated with @mcp.tool() for automatic registration in FastMCP. It authenticates using credentials from env vars, creates an alphaess client, calls client.authenticate(), and returns success/failure dict.
    @mcp.tool()
    async def authenticate_alphaess() -> dict[str, Any]:
        """
        Authenticate with the Alpha ESS Open API to validate credentials.
        
        Returns:
            dict: Authentication result with success status and message
        """
        client = None
        try:
            app_id, app_secret = get_alpha_credentials()
    
            # Create Alpha ESS client instance with credentials
            client = alphaess(app_id, app_secret)
    
            # Attempt authentication
            auth_result = await client.authenticate()
    
            if auth_result:
                return {
                    "success": True,
                    "message": "Successfully authenticated with Alpha ESS API",
                    "authenticated": True
                }
            else:
                return {
                    "success": False,
                    "message": "Authentication failed - invalid credentials or API error",
                    "authenticated": False
                }
    
        except ValueError as e:
            return {
                "success": False,
                "message": f"Configuration error: {str(e)}",
                "authenticated": False
            }
        except Exception as e:
            return {
                "success": False,
                "message": f"Unexpected error during authentication: {str(e)}",
                "authenticated": False
            }
        finally:
            # Clean up the client connection
            if client:
                await client.close()
  • Helper function to retrieve Alpha ESS app_id and app_secret from environment variables, used by the authenticate_alphaess handler.
    def get_alpha_credentials():
        """Get Alpha ESS credentials from environment variables"""
        app_id = os.getenv('ALPHA_ESS_APP_ID')
        app_secret = os.getenv('ALPHA_ESS_APP_SECRET')
    
        if not app_id or not app_secret:
            raise ValueError("ALPHA_ESS_APP_ID and ALPHA_ESS_APP_SECRET environment variables must be set")
    
        return app_id, app_secret
  • main.py:310-310 (registration)
    The @mcp.tool() decorator registers the authenticate_alphaess function as an MCP tool.
    @mcp.tool()
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the core behavior (authentication and validation) and return type (dict with success status and message), which is helpful. However, it doesn't mention potential side effects (e.g., session creation), error conditions, or rate limits, leaving some behavioral aspects unclear.

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 extremely concise and well-structured: one sentence for the purpose and one for the return value. Every sentence earns its place, with no wasted words. It's appropriately sized for a simple authentication tool.

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

Completeness4/5

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

Given the tool's low complexity (0 parameters, authentication-only), the description is reasonably complete. It explains what the tool does and what it returns. With an output schema present, it doesn't need to detail return values further. However, it could benefit from mentioning prerequisites (e.g., required credentials) or error handling for a more complete context.

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

Parameters4/5

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

The tool has 0 parameters, and schema description coverage is 100%. The description doesn't need to add parameter semantics beyond what the schema provides (none). A baseline of 4 is appropriate for zero-parameter tools, as there's no parameter documentation burden.

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: 'Authenticate with the Alpha ESS Open API to validate credentials.' It specifies the verb ('authenticate') and resource ('Alpha ESS Open API'), and distinguishes it from sibling tools which are all data retrieval or configuration tools. However, it doesn't explicitly differentiate from potential alternative authentication methods, keeping it at 4 rather than 5.

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 context (authentication for API access) but doesn't explicitly state when to use this tool versus alternatives. Given that all sibling tools are data/configuration operations, it's reasonable to infer this should be used first for credential validation, but this isn't explicitly stated. No misleading guidance is present.

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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