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Enkrypt AI MCP Server

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get_deployment_details

Retrieve specific deployment details by name to monitor and manage configurations effectively. Enables clear insights into deployment settings and status for better operational control.

Instructions

Retrieve details of a specific deployment using its name.

Args: deployment_name: The name of the deployment to retrieve details for.

Returns: A dictionary containing the details of the deployment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deployment_nameYes

Implementation Reference

  • The core handler function for the 'get_deployment_details' tool. It is registered via the @mcp.tool() decorator and implements the tool logic by calling deployment_client.get_deployment() to fetch and return deployment details as a dictionary.
    @mcp.tool()
    def get_deployment_details(deployment_name: str) -> Dict[str, Any]:
        """
        Retrieve details of a specific deployment using its name.
    
        Args:
            deployment_name: The name of the deployment to retrieve details for.
    
        Returns:
            A dictionary containing the details of the deployment.
        """
        # Retrieve deployment details
        deployment_details = deployment_client.get_deployment(deployment_name=deployment_name)
    
        # Return the deployment details as a dictionary
        return deployment_details.to_dict()
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a retrieval operation but doesn't mention whether it requires authentication, has rate limits, what happens if the deployment doesn't exist, or the structure of returned details. For a read operation with zero annotation coverage, this leaves significant behavioral gaps.

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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence earns its place, with no redundant information. The three-part format (purpose, parameter, return) is well-organized and appropriately sized for a single-parameter tool.

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

Completeness3/5

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

For a single-parameter read operation with no annotations and no output schema, the description provides adequate basic information but lacks important context. It doesn't explain what 'details' include in the return dictionary, error conditions, or how this tool relates to other deployment tools like 'modify_deployment_config' or 'remove_deployment'. The description is minimally viable but has clear gaps.

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?

Schema description coverage is 0%, so the description must compensate. It clearly explains the single parameter 'deployment_name' as 'The name of the deployment to retrieve details for', adding meaningful context beyond the schema's basic type information. However, it doesn't specify format constraints or provide examples, preventing a perfect score.

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 action ('Retrieve details') and target resource ('specific deployment using its name'), making the purpose unambiguous. It distinguishes from sibling 'list_deployments' by focusing on a single deployment rather than listing multiple. However, it doesn't specify what 'details' include, which prevents a perfect score.

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 when you need details for a specific deployment (vs. 'list_deployments' for multiple deployments), but doesn't explicitly state when to use this tool versus alternatives like 'get_model_details' or 'get_redteam_task_details'. No exclusions or prerequisites are mentioned, leaving some ambiguity about appropriate contexts.

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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