Skip to main content
Glama
xmpuspus

cloudwright-mcp

by xmpuspus
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

list_services

List all cloud services for a provider. Returns slug, name, category, and supported tiers. Use to find valid service keys for ArchSpecs or requirement mapping.

Instructions

List all cloud services supported for a given provider.

Returns one entry per service with its slug, human-readable name, category (compute / database / storage / networking / etc.), and supported tiers. Use this to discover valid service: keys when hand-authoring ArchSpecs or mapping requirements to services.

Behavior: Pure lookup from the bundled service registry — no LLM, no network, no cloud access.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerNoCloud provider slug. Values: 'aws' (47 services), 'gcp' (25), 'azure' (28), 'databricks'.aws

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • packages/mcp/cloudwright_mcp/tools/export.py:58-83 (handler)
    The MCP tool handler function for 'list_services'. Uses a decorator-based registration (@mcp.tool()) and calls ServiceRegistry().list_services(provider) to return cloud services for a given provider as a list of dicts.
    @mcp.tool()
def list_services(
    provider: Annotated[
        str,
        Field(
            description=(
                "Cloud provider slug. Values: 'aws' (47 services), 'gcp' (25), 'azure' (28), 'databricks'."
            ),
            examples=["aws", "gcp", "azure", "databricks"],
        ),
    ] = "aws",
) -> list[dict]:
    """List all cloud services supported for a given provider.

    Returns one entry per service with its slug, human-readable name, category
    (compute / database / storage / networking / etc.), and supported tiers.
    Use this to discover valid `service:` keys when hand-authoring ArchSpecs
    or mapping requirements to services.

    Behavior: Pure lookup from the bundled service registry — no LLM, no
    network, no cloud access.
    """
    from cloudwright.registry import ServiceRegistry

    services = ServiceRegistry().list_services(provider)
    return [s.to_dict() for s in services]
  • packages/mcp/cloudwright_mcp/tools/export.py:9-10 (registration)
    The register() function in export.py that decorates tool functions (including list_services) with @mcp.tool() to register them with the FastMCP server.
    def register(mcp: FastMCP) -> None:
    @mcp.tool()

Tool Definition Quality

A4.7/5.0
Behavior5/5

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

Without annotations, the description fully discloses behavior: pure local lookup with no LLM, network, or cloud access. This addresses potential concerns about side effects, latency, or dependencies.

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?

Four succinct sentences: purpose, output details, usage guidance, behavior. No wasted words, front-loaded with key information.

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

Completeness5/5

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

Given the tool's simplicity (one optional parameter, output schema exists), the description covers all necessary context: what it returns, when to use it, and how it behaves. No gaps remain.

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?

With 100% schema coverage, the description adds value by connecting the parameter to the use case of discovering service keys. It doesn't repeat schema details but reinforces the tool's purpose.

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 lists all cloud services for a provider, specifying return fields like slug, name, category, and tiers. It distinguishes itself from sibling tools (e.g., design_architecture, estimate_cost) by being a pure lookup tool.

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 explicitly advises using the tool to discover valid service keys for ArchSpecs or requirement mapping, providing clear context. It could be improved by mentioning when not to use it, but the use case is well articulated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/xmpuspus/cloudwright'

If you have feedback or need assistance with the MCP directory API, please join our Discord server