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check_service_status

Check the current status of any cloud service by entering its name. Returns real-time availability from the official status page.

Instructions

Check the current status of a cloud service (via its status page).

Args: service_name: The service name — e.g. "github", "stripe", "openai", "cloudflare", "vercel"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
service_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The tool handler function 'check_service_status' that queries the Grounded API for the current status of a cloud service (e.g. github, stripe, openai).
    async def check_service_status(service_name: str) -> str:
        """Check the current status of a cloud service (via its status page).
    
        Args:
            service_name: The service name — e.g. "github", "stripe", "openai", "cloudflare", "vercel"
        """
        return await _query_fact("statuspage", service_name, "status")
  • The tool is registered via the '@mcp.tool()' decorator on the async function, using FastMCP.
    @mcp.tool()
    async def check_service_status(service_name: str) -> str:
  • The helper function '_query_fact' that makes HTTP requests to the Grounded API and formats the response. Called by check_service_status.
    async def _query_fact(source: str, entity: str, field: str) -> str:
        """Query the Grounded API and return a formatted result."""
        headers = {}
        if API_KEY:
            headers["X-API-Key"] = API_KEY
        async with httpx.AsyncClient() as client:
            resp = await client.get(
                f"{API_BASE}/v1/fact",
                params={"source": source, "entity": entity, "field": field},
                headers=headers,
                timeout=10.0,
            )
    
        if resp.status_code == 200:
            data = resp.json()
            return (
                f"Value: {data['value']}\n"
                f"Source: {data['source_url']}\n"
                f"Fetched at: {data['fetched_at']}\n"
                f"Hash: {data['raw_response_hash']}\n"
                f"Tier: {data['tier']} (TTL: {data['ttl_seconds']}s)"
            )
        elif resp.status_code == 404:
            detail = resp.json().get("detail", "Not found")
            return f"Not found: {detail}"
        else:
            return f"Error: HTTP {resp.status_code}"
  • The docstring serves as the schema definition for the tool, describing the 'service_name' parameter and listing valid cloud services.
    """Check the current status of a cloud service (via its status page).
    
    Args:
        service_name: The service name — e.g. "github", "stripe", "openai", "cloudflare", "vercel"
    """
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'via its status page' but lacks details about the mechanism (e.g., HTTP request, possible delays, caching) or what the returned status looks like. For a check tool, more transparency about output format or potential errors would be beneficial.

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?

Extremely concise: two sentences with purpose and parameter description. No extraneous words; front-loaded with the action. Every sentence earns its place.

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 simplicity (one parameter, clear purpose) and the presence of an output schema, the description is largely complete. It could optionally describe the return type, but the output schema likely covers that. The description adequately supports an agent in using the tool.

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?

Only one parameter (service_name), and schema coverage is 0%. The description adds value by listing example service names, which clarifies valid inputs beyond the schema's type string. However, it does not specify format requirements (e.g., case sensitivity or exact naming).

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?

Clearly states the tool's purpose: checking the current status of a cloud service via its status page. The verb 'Check' and resource 'status of a cloud service' are specific. It is distinct from sibling tools that deal with downloads, package versions, or facts.

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

Usage Guidelines4/5

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

Provides concrete examples of service names (e.g., 'github', 'stripe'). Implies when to use: when you need to verify service health. Does not explicitly state when not to use or contrast with alternatives, but the clear purpose and examples offer sufficient guidance for this simple tool.

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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