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jamesbrink

MCP Server for Coroot

update_custom_cloud_pricing

Set custom pricing for cloud resources to override default costs. Provide project ID and pricing configuration.

Instructions

Update custom cloud pricing configuration.

Sets custom pricing for cloud resources to override default pricing.

Args: project_id: Project ID pricing: Custom pricing configuration

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
pricingYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool registration (decorated with @mcp.tool()) - the public entry point that delegates to the implementation function.
    @mcp.tool()
    async def update_custom_cloud_pricing(
        project_id: str, pricing: dict[str, Any]
    ) -> dict[str, Any]:
        """Update custom cloud pricing configuration.
    
        Sets custom pricing for cloud resources to override default pricing.
    
        Args:
            project_id: Project ID
            pricing: Custom pricing configuration
        """
        return await update_custom_cloud_pricing_impl(project_id, pricing)  # type: ignore[no-any-return]
  • Implementation function (update_custom_cloud_pricing_impl) with error handling via @handle_errors decorator. Calls the client method and formats the response.
    @handle_errors
    async def update_custom_cloud_pricing_impl(
        project_id: str, pricing: dict[str, Any]
    ) -> dict[str, Any]:
        """Update custom cloud pricing."""
        client = get_client()
        result = await client.update_custom_cloud_pricing(project_id, pricing)
        return {
            "success": True,
            "message": "Custom cloud pricing updated successfully",
            "pricing": result,
        }
  • Client method on CorootClient that performs the actual HTTP request (POST /api/project/{project_id}/custom_cloud_pricing) with the pricing payload.
    async def update_custom_cloud_pricing(
        self, project_id: str, pricing: dict[str, Any]
    ) -> dict[str, Any]:
        """Update custom cloud pricing configuration.
    
        Args:
            project_id: Project ID.
            pricing: Custom pricing configuration.
    
        Returns:
            Updated pricing configuration.
        """
        response = await self._request(
            "POST", f"/api/project/{project_id}/custom_cloud_pricing", json=pricing
        )
        return self._parse_json_response(response)
Behavior2/5

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

No annotations are present, so the description must fully disclose behavioral traits. It indicates a mutation ('update', 'sets') but does not mention side effects, required permissions, or the reversible nature of the operation. The lack of detail on behavioral consequences is a significant gap.

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?

The description is brief with two sentences plus an Args list, which is appropriately sized. The main action is front-loaded. However, some of the space could be better used to add missing details, slightly reducing efficiency.

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

Completeness2/5

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

Given the complexity of the pricing object and lack of annotations, the description is insufficient. It does not explain the return value (though output schema exists), validation rules, or what constitutes a valid pricing configuration. A more complete description would include constraints or examples for the pricing parameter.

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

Parameters2/5

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

The input schema has 0% description coverage, placing the burden on the description to clarify each parameter. The description provides minimal labels ('Project ID', 'Custom pricing configuration') but fails to explain the structure or expected keys of the pricing object (additionalProperties: true). This offers little beyond the schema property names.

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 states 'Update custom cloud pricing configuration' and 'Sets custom pricing for cloud resources to override default pricing.' This clearly identifies the verb (update) and resource (custom cloud pricing), and distinguishes it from sibling tools like delete_custom_cloud_pricing and get_custom_cloud_pricing.

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 guidance is provided on when to use this tool versus alternatives such as delete or get. The description does not specify prerequisites, limitations, or exclusion criteria, leaving the agent without decision support for tool selection.

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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