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jamesbrink

MCP Server for Coroot

update_custom_applications

Update custom application configurations in Coroot to group instances by container name patterns for better monitoring organization.

Instructions

Update custom applications configuration.

Updates the list of custom application definitions. Custom applications allow grouping instances by container name patterns.

Args: project_id: Project ID applications: New custom applications list with instance patterns

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
applicationsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler: the @mcp.tool()-decorated function that handles tool invocation and delegates to the implementation wrapper.
    @mcp.tool()
    async def update_custom_applications(
        project_id: str,
        applications: dict[str, Any],
    ) -> dict[str, Any]:
        """Update custom applications configuration.
    
        Updates the list of custom application definitions. Custom applications
        allow grouping instances by container name patterns.
    
        Args:
            project_id: Project ID
            applications: New custom applications list with instance patterns
        """
        return await update_custom_applications_impl(  # type: ignore[no-any-return]
            project_id, applications
        )
  • Error-handling wrapper implementation that invokes the CorootClient method and formats the response.
    @handle_errors
    async def update_custom_applications_impl(
        project_id: str,
        applications: dict[str, Any],
    ) -> dict[str, Any]:
        """Update custom applications."""
        result = await get_client().update_custom_applications(project_id, applications)
        return {
            "success": True,
            "message": "Custom applications updated successfully",
            "applications": result,
        }
  • Coroot API client method implementing the HTTP POST request to the Coroot API endpoint for updating custom applications.
    async def update_custom_applications(
        self, project_id: str, applications: dict[str, Any]
    ) -> dict[str, Any]:
        """Update custom applications configuration.
    
        Args:
            project_id: Project ID.
            applications: New custom applications configuration.
    
        Returns:
            Updated applications.
        """
        response = await self._request(
            "POST", f"/api/project/{project_id}/custom_applications", json=applications
        )
        data: dict[str, Any] = response.json()
        return data
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Updates the list,' implying a mutation that overwrites or modifies existing configurations, but doesn't specify permissions needed, whether changes are reversible, rate limits, or what happens to existing patterns not included. This is inadequate for a mutation tool with zero annotation coverage.

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 front-loaded with the core purpose in the first sentence, followed by explanatory context and an Args section. It avoids unnecessary fluff, but the Args section could be integrated more seamlessly. Overall, it's efficient with minimal waste.

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?

Given the tool has an output schema (which handles return values), no annotations, and 2 parameters with 0% schema coverage, the description provides basic purpose and parameter hints. However, as a mutation tool, it lacks critical behavioral details like side effects or prerequisites, making it incomplete for safe agent use despite the output schema.

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

Parameters3/5

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

Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds value by explaining 'project_id: Project ID' and 'applications: New custom applications list with instance patterns,' giving basic semantics. However, it doesn't detail the structure of 'applications' (e.g., format of instance patterns) or provide examples, leaving gaps for a nested object parameter.

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 ('Update') and resource ('custom applications configuration'), specifying that it updates the list of custom application definitions. It distinguishes from sibling tools like 'get_custom_applications' by indicating a write operation, though it doesn't explicitly differentiate from other 'update_' tools like 'update_application_category'.

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?

The description provides no guidance on when to use this tool versus alternatives. It mentions that custom applications 'allow grouping instances by container name patterns,' which hints at context, but lacks explicit when/when-not instructions or references to sibling tools like 'create_custom_applications' (if it existed) or 'get_custom_applications'.

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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