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gigapi

GigAPI MCP Server

by gigapi

health_check

Check the health status of the GigAPI server to verify its operational state and availability for managing timeseries data.

Instructions

Check the health status of the GigAPI server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_Yes

Implementation Reference

  • The main handler function for the 'health_check' MCP tool. It invokes the client's health_check method and formats the response with success status.
    def health_check(self) -> Dict[str, Any]:
        """Check GigAPI server health.
    
        Returns:
            Health status
        """
        try:
            health = self.client.health_check()
            return {
                "health": health,
                "success": True,
                "status": "healthy"
            }
        except GigAPIClientError as e:
            logger.error(f"Health check failed: {e}")
            return {
                "error": str(e),
                "success": False,
                "status": "unhealthy"
            }
  • Registration of the 'health_check' tool using FastMCP's Tool.from_function, binding the GigAPITools.health_check method.
    Tool.from_function(
        lambda _: tools_instance.health_check(),
        name="health_check",
        description="Check the health status of the GigAPI server.",
    ),
  • Helper method in GigAPIClient that performs the actual HTTP GET request to '/health' endpoint and returns the JSON response.
    def health_check(self) -> Dict[str, Any]:
        """Check GigAPI server health.
    
        Returns:
            Health status response
        """
        response = self._make_request("GET", "/health")
        return response.json()
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks health status, which implies a read-only operation, but doesn't specify what 'health status' entails (e.g., uptime, metrics, error states), whether it requires authentication, or how results are returned. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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, clear sentence that efficiently conveys the core purpose without unnecessary details. It is appropriately sized and front-loaded, with every word contributing to understanding the tool's function. No waste or redundancy is present.

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 the tool's simplicity (one parameter, no output schema, no annotations), the description is incomplete. It doesn't explain the parameter's purpose, the expected output format, or behavioral aspects like error handling. While the tool might be straightforward, the description lacks sufficient detail for an agent to use it confidently without additional context.

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?

The input schema has one required parameter '_' with 0% description coverage, meaning the schema provides no details about this parameter. The description adds no information about parameters, failing to compensate for the lack of schema documentation. This leaves the agent with no guidance on what the parameter represents or how to use it.

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: 'Check the health status of the GigAPI server.' It uses a specific verb ('Check') and identifies the resource ('GigAPI server'), though it doesn't explicitly differentiate from sibling tools like 'ping' which might serve a similar purpose. The description avoids tautology by not just restating the tool name.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'ping' that might overlap in functionality, nor does it specify any prerequisites or contexts for usage. The agent must infer usage based on the tool name and description alone.

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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