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jamesbrink

MCP Server for Coroot

get_nodes_overview

Monitor infrastructure node health, resource usage, running containers, and system metrics to identify performance issues and optimize resource allocation.

Instructions

Get overview of infrastructure nodes.

Returns information about all nodes in the infrastructure:

  • Node health and status

  • Resource utilization

  • Running containers

  • System metrics

Args: project_id: Project ID query: Search/filter query (optional)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
queryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Primary MCP tool handler: the @mcp.tool()-decorated function that executes the tool logic by delegating to the implementation wrapper and ultimately to the CorootClient.
    @mcp.tool()
    async def get_nodes_overview(
        project_id: str,
        query: str | None = None,
    ) -> dict[str, Any]:
        """Get overview of infrastructure nodes.
    
        Returns information about all nodes in the infrastructure:
        - Node health and status
        - Resource utilization
        - Running containers
        - System metrics
    
        Args:
            project_id: Project ID
            query: Search/filter query (optional)
        """
        return await get_nodes_overview_impl(project_id, query)  # type: ignore[no-any-return]
  • Helper method in CorootClient that performs the actual HTTP API request to retrieve nodes overview data from the Coroot server.
    async def get_nodes_overview(
        self,
        project_id: str,
        query: str | None = None,
    ) -> dict[str, Any]:
        """Get infrastructure nodes overview.
    
        Args:
            project_id: Project ID.
            query: Search/filter query.
    
        Returns:
            Nodes overview data.
        """
        params = {}
        if query:
            params["query"] = query
    
        response = await self._request(
            "GET",
            f"/api/project/{project_id}/overview/nodes",
            params=params,
        )
        data: dict[str, Any] = response.json()
        return data
  • Internal implementation wrapper that calls the CorootClient method and formats the response with success indicator.
    @handle_errors
    async def get_nodes_overview_impl(
        project_id: str,
        query: str | None = None,
    ) -> dict[str, Any]:
        """Get nodes overview."""
        overview = await get_client().get_nodes_overview(project_id, query)
        return {
            "success": True,
            "overview": overview,
        }
  • FastMCP tool registration decorator applied to the handler function.
    @mcp.tool()
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 mentions the return information (health, utilization, etc.) but lacks critical details such as whether this is a read-only operation, if it requires specific permissions, rate limits, pagination, or error handling. The description is insufficient for a tool that likely accesses infrastructure data.

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 appropriately sized and front-loaded, starting with the purpose and followed by a bulleted list of returns and parameter explanations. Every sentence adds value, with no redundant information, though it could be slightly more structured with clearer sections.

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's complexity (infrastructure overview with 2 parameters), no annotations, and an output schema present (which covers return values), the description is moderately complete. It explains what information is returned and parameter semantics but lacks behavioral context and usage guidelines, making it adequate but with clear gaps for an infrastructure tool.

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 description must compensate. It adds meaning by explaining 'project_id' as 'Project ID' and 'query' as an optional 'Search/filter query', which clarifies their roles. However, it doesn't provide format examples, constraints, or how the query parameter works, leaving gaps in understanding.

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's purpose with a specific verb ('Get overview') and resource ('infrastructure nodes'), and it details the information returned (health, resource utilization, containers, metrics). However, it doesn't explicitly differentiate from sibling tools like 'get_node' (singular) or 'get_applications_overview', leaving some ambiguity about scope.

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 doesn't mention sibling tools like 'get_node' (for single node details) or 'get_applications_overview', nor does it specify prerequisites or contexts for usage, relying solely on the tool name and description.

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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