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Apollo.io MCP Server

health_check

Verify the Apollo.io API connection status and authentication validity to ensure reliable access for sales and marketing operations.

Instructions

Check the health and authentication status of the Apollo.io API connection.

This tool verifies that the API key is valid and the service is accessible.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The health_check tool handler function, decorated with @mcp.tool() which registers it in the FastMCP server. It performs a health check by making a GET request to Apollo.io's /v1/auth/health endpoint and returns the result or an error message.
    @mcp.tool()
    async def health_check() -> Dict[str, Any]:
        """
        Check the health and authentication status of the Apollo.io API connection.
        
        This tool verifies that the API key is valid and the service is accessible.
        """
        endpoint = "/v1/auth/health"
        
        try:
            result = await apollo_client.make_request("GET", endpoint)
            return result
        except httpx.HTTPStatusError as e:
            return {"error": f"API request failed: {e.response.status_code} {e.response.text}"}
        except Exception as e:
            return {"error": f"Request failed: {str(e)}"}
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 tool's behavior as a read-only diagnostic check ('check', 'verify'), which is appropriate, but lacks details like rate limits, error responses, or specific output format. The description adds basic context without contradictions, but more behavioral traits could be included.

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 appropriately sized with two concise sentences that are front-loaded with the main purpose. Every sentence adds value by explaining what the tool does and its specific checks, with zero waste or unnecessary details.

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, simple diagnostic purpose) and the presence of an output schema, the description is mostly complete. It covers the purpose and usage context adequately, but could benefit from more behavioral details like what 'health' entails or authentication specifics, though the output schema may handle return values.

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%, so no parameter information is needed. The description does not mention parameters, which is acceptable, earning a baseline score of 4 for not introducing confusion or redundancy.

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?

The description clearly states the tool's purpose with specific verbs ('check', 'verify') and resources ('health and authentication status', 'API connection', 'API key', 'service accessibility'). It distinguishes itself from sibling tools by focusing on system diagnostics rather than data operations like enrichment, search, or updates.

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?

The description implies usage context for verifying API connectivity and authentication validity, which is clear guidance for when to use this tool. However, it does not explicitly state when not to use it or name specific alternatives among the siblings, such as distinguishing from data retrieval tools that might also fail due to auth issues.

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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