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wagonbomb

Megaraptor MCP

by wagonbomb

get_deployment_status

Check deployment status and health by providing a deployment ID to monitor metrics and ensure operational integrity.

Instructions

Check the status and health of a deployment.

Args: deployment_id: The deployment identifier (e.g., 'vr-20240115-a1b2c3d4')

Returns: Current deployment status including health checks and metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deployment_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The implementation of the get_deployment_status MCP tool. It validates the deployment ID, attempts to retrieve the status using DockerDeployer and then BinaryDeployer, performs a health check, and returns the combined results.
    async def get_deployment_status(
        deployment_id: str,
    ) -> list[TextContent]:
        """Check the status and health of a deployment.
    
        Args:
            deployment_id: The deployment identifier (e.g., 'vr-20240115-a1b2c3d4')
    
        Returns:
            Current deployment status including health checks and metrics.
        """
        try:
            # Validate deployment_id
            deployment_id = validate_deployment_id(deployment_id)
    
            from ..deployment.deployers import DockerDeployer, BinaryDeployer
    
            # Try Docker first
            deployer = DockerDeployer()
            info = await deployer.get_status(deployment_id)
    
            if info:
                health = await deployer.health_check(deployment_id)
                return [TextContent(
                    type="text",
                    text=json.dumps({
                        **info.to_dict(),
                        "health": health,
                    }, indent=2, default=str)
                )]
    
            # Try binary deployer
            deployer = BinaryDeployer()
            info = await deployer.get_status(deployment_id)
    
            if info:
                health = await deployer.health_check(deployment_id)
                return [TextContent(
                    type="text",
                    text=json.dumps({
                        **info.to_dict(),
                        "health": health,
                    }, indent=2, default=str)
                )]
    
            return [TextContent(
                type="text",
                text=json.dumps({
                    "error": f"Deployment not found: {deployment_id}",
                    "hint": "Use list_deployments tool to see available deployments"
                }, indent=2)
            )]
    
        except ValueError as e:
            # Validation errors
            return [TextContent(
                type="text",
                text=json.dumps({
                    "error": str(e),
                    "hint": "Provide a valid deployment ID starting with 'vr-'"
                }, indent=2)
            )]
    
        except ImportError as e:
            return [TextContent(
                type="text",
                text=json.dumps({
                    "error": f"Missing dependency: {str(e)}",
                    "hint": "Install required packages with: pip install megaraptor-mcp[deployment]"
                }, indent=2)
            )]
    
        except Exception:
            # Generic errors - don't expose internals
            return [TextContent(
                type="text",
                text=json.dumps({
                    "error": "Failed to get deployment status",
                    "hint": "Check deployment ID and try again"
                }, indent=2)
            )]
Behavior3/5

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

No annotations provided, so description carries full burden. It mentions the return includes 'health checks and metrics' which adds context, but lacks explicit safety disclosure (read-only vs destructive), error handling behavior (e.g., deployment not found), or rate limiting details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear Args/Returns sections. Front-loaded with the core purpose. The Args section is necessary given 0% schema coverage. The Returns section is somewhat redundant given the output schema exists, but remains brief.

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?

Adequate for a single-parameter read operation with an output schema (which handles return value documentation). However, gaps remain regarding error conditions and safety characteristics, which are unaddressed due to missing annotations.

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%, requiring the description to compensate. The Args section effectively documents the deployment_id parameter with a clear example format ('vr-20240115-a1b2c3d4'), explaining the expected identifier pattern that the schema omits.

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 'Check[s] the status and health of a deployment' with specific verbs and resource. It distinguishes from siblings like list_deployments (this retrieves a specific deployment by ID) and destroy_deployment (destructive action), though it could more explicitly differentiate from check_agent_deployment.

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?

No explicit guidance on when to use this tool versus alternatives like validate_deployment or check_agent_deployment. No mention of prerequisites (e.g., obtaining deployment_id from list_deployments) or when not to use it.

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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