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wagonbomb

Megaraptor MCP

by wagonbomb
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Python
Remote

deploy_server_cloud

Deploy a Velociraptor server on AWS or Azure cloud infrastructure using CloudFormation or ARM templates for digital forensics and incident response.

Instructions

Deploy Velociraptor server on cloud infrastructure.

Deploys using CloudFormation (AWS) or ARM templates (Azure).

Args: cloud_provider: Cloud provider - 'aws' or 'azure' profile: Deployment profile ('standard' or 'enterprise') region: Cloud region (defaults to us-east-1 for AWS, eastus for Azure) instance_type: VM instance type (auto-selected based on profile) server_hostname: Hostname for server (defaults to public IP)

Returns: Deployment details including cloud resource IDs and URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cloud_providerYes
profileNostandard
regionNo
instance_typeNo
server_hostnameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • src/megaraptor_mcp/tools/deployment.py:218-243 (handler)
    The handler function deploy_server_cloud acts as a wrapper for deploy_server, allowing cloud-specific deployment parameters.
    async def deploy_server_cloud(
    cloud_provider: str,
    profile: str = "standard",
    region: Optional[str] = None,
    instance_type: Optional[str] = None,
    server_hostname: Optional[str] = None,
) -> list[TextContent]:
    """Deploy Velociraptor server on cloud infrastructure.

    Deploys using CloudFormation (AWS) or ARM templates (Azure).

    Args:
        cloud_provider: Cloud provider - 'aws' or 'azure'
        profile: Deployment profile ('standard' or 'enterprise')
        region: Cloud region (defaults to us-east-1 for AWS, eastus for Azure)
        instance_type: VM instance type (auto-selected based on profile)
        server_hostname: Hostname for server (defaults to public IP)

    Returns:
        Deployment details including cloud resource IDs and URLs.
    """
    return await deploy_server(
        deployment_type=cloud_provider,
        profile=profile,
        server_hostname=server_hostname or "localhost",
    )

Tool Definition Quality

A4.1/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It successfully discloses implementation mechanism (CloudFormation/ARM templates) and return value structure ('cloud resource IDs and URLs'), but omits critical behavioral traits for a deployment tool: permission requirements, cost implications, idempotency guarantees, and timeout 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 optimally structured with a clear one-sentence purpose statement, implementation detail, and structured Args/Returns sections. Every sentence earns its place; there is no redundant or verbose text while maintaining completeness.

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?

The description adequately covers all 5 parameters and acknowledges return values (complemented by the presence of an output schema). However, for a cloud deployment operation of this complexity, it lacks prerequisite context such as required IAM permissions, credential configuration, or potential cost implications, preventing a perfect score.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Given 0% schema description coverage, the Args section provides comprehensive compensation by documenting all 5 parameters: valid enum values for 'cloud_provider' ('aws' or 'azure') and 'profile' ('standard' or 'enterprise'), plus default behaviors for 'region', 'instance_type', and 'server_hostname'. This fully bridges the schema gap.

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 opens with a specific action ('Deploy') and resource ('Velociraptor server') scoped to 'cloud infrastructure'. It further distinguishes from siblings like 'deploy_server_docker' and 'deploy_server' by specifying the implementation technologies: 'CloudFormation (AWS) or ARM templates (Azure)', making the deployment target unambiguous.

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?

While the description implies cloud-specific usage through the mention of AWS/Azure technologies and the 'cloud_provider' argument, it lacks explicit guidance on when to choose this over sibling tools like 'deploy_server_docker' or 'deploy_server'. The Args section provides implicit context but no explicit 'when to use' directives.

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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