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SlideSpeak
by SlideSpeak

get_me

Retrieve current API key details: user name and remaining credits to track usage.

Instructions

Get details about the current API key (user_name and remaining credits).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler for the 'get_me' tool. Calls the SlideSpeak API GET /me endpoint to fetch current user details (user_name and remaining credits) and returns them as JSON with a note about credit usage.
    @mcp.tool()
    async def get_me() -> str:
        """
        Get details about the current API key (user_name and remaining credits).
        """
        if not API_KEY:
            return "API Key is missing. Cannot process any requests."
    
        result = await _make_api_request("GET", "/me")
        if not result:
            return "Failed to fetch current user details."
        return json.dumps(result) + "\n Note: Generating slides costs 1 credit / slide"
  • slidespeak.py:108-109 (registration)
    Registration of the 'get_me' tool using the @mcp.tool() decorator on the FastMCP server instance.
    @mcp.tool()
    async def get_me() -> str:
  • Helper function used by get_me to make HTTP requests to the SlideSpeak API. Handles authentication via X-API-Key header, error logging, and response parsing.
    async def _make_api_request(
        method: Literal["GET", "POST"],
        endpoint: str,
        payload: Optional[dict[str, Any]] = None,
        timeout: float = DEFAULT_TIMEOUT
    ) -> Optional[dict[str, Any]]:
        """
        Makes an HTTP request to the SlideSpeak API.
    
        Args:
            method: HTTP method ('GET' or 'POST').
            endpoint: API endpoint path (e.g., '/presentation/templates').
            payload: JSON payload for POST requests. Ignored for GET.
            timeout: Request timeout in seconds.
    
        Returns:
            The parsed JSON response as a dictionary on success, None on failure.
        """
        if not API_KEY:
            logging.error("API Key is missing. Cannot make API request.")
            return None
    
        headers = {
            "User-Agent": USER_AGENT,
            "Accept": "application/json",
            "X-API-Key": API_KEY,
        }
    
        url = f"{API_BASE}{endpoint}"
        req_start = time.time()
    
        async with httpx.AsyncClient() as client:
            try:
                if method == "POST":
                    response = await client.post(url, json=payload, headers=headers, timeout=timeout)
                else:
                    response = await client.get(url, headers=headers, timeout=timeout)
    
                elapsed = time.time() - req_start
                logging.info(f"{method} {url} | status={response.status_code} | elapsed={elapsed:.2f}s")
                response.raise_for_status()
                return response.json()
    
            except httpx.HTTPStatusError as e:
                logging.error(f"HTTP error {method} {url}: {e.response.status_code} - {e.response.text}")
            except httpx.RequestError as e:
                logging.error(f"Request error {method} {url}: {str(e)}")
            except Exception as e:
                logging.error(f"Unexpected error {method} {url}: {str(e)}")
    
            return None
Behavior3/5

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

The description discloses the returned fields (user_name and remaining credits) and implies a read-only, safe operation. No annotations exist, so it carries full burden, but it lacks details about possible failures or rate limiting.

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?

Single sentence, no wasted words, clearly front-loaded with purpose and output details.

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

Completeness5/5

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

For a simple, parameterless tool with no nested objects or enums, the description fully covers its purpose and output. No output schema but description compensates.

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?

Input schema has 0 parameters, so description adds no param info. With schema coverage at 100%, baseline is 4; no extra credit needed.

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?

Description clearly states verb 'Get', resource 'current API key', and outputs 'user_name and remaining credits'. It's distinct from sibling tools which deal with presentations and templates.

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?

No explicit guidance on when to use vs alternatives, but the specific purpose implies it's for querying API key details. Siblings are very different, so confusion is unlikely.

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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