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jamesbrink

MCP Server for Coroot

get_node

Retrieve comprehensive metrics and health status for a specific infrastructure node, including resource usage, running containers, and system information.

Instructions

Get detailed information about a specific infrastructure node.

Retrieves comprehensive metrics and information about a node including:

  • Resource usage (CPU, memory, disk, network)

  • Running containers

  • System information

  • Health status

Args: project_id: Project ID node_id: Node ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
node_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool registration for 'get_node' using @mcp.tool() decorator
    @mcp.tool()
    async def get_node(project_id: str, node_id: str) -> dict[str, Any]:
        """Get detailed information about a specific infrastructure node.
    
        Retrieves comprehensive metrics and information about a node including:
        - Resource usage (CPU, memory, disk, network)
        - Running containers
        - System information
        - Health status
    
        Args:
            project_id: Project ID
            node_id: Node ID
        """
        return await get_node_impl(project_id, node_id)  # type: ignore[no-any-return]
  • Handler implementation that calls the CorootClient.get_node and formats the response
    @handle_errors
    async def get_node_impl(project_id: str, node_id: str) -> dict[str, Any]:
        """Get node details."""
        node = await get_client().get_node(project_id, node_id)
        return {
            "success": True,
            "node": node,
        }
  • CorootClient helper method that performs the HTTP GET request to retrieve node details from the Coroot API
    async def get_node(self, project_id: str, node_id: str) -> dict[str, Any]:
        """Get detailed information about a specific node.
    
        Args:
            project_id: Project ID.
            node_id: Node ID.
    
        Returns:
            Node details including metrics and containers.
        """
        response = await self._request(
            "GET", f"/api/project/{project_id}/node/{node_id}"
        )
        data: dict[str, Any] = response.json()
        return data
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 of behavioral disclosure. It clearly indicates this is a read operation ('Retrieves') and specifies the scope of data returned (resource usage, containers, etc.), which is helpful. However, it doesn't mention potential limitations like rate limits, authentication requirements, or error conditions, leaving gaps for a tool with no 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose. The bullet points efficiently detail the information retrieved without redundancy, and the Args section cleanly lists parameters. Every sentence adds value, with no wasted words or unnecessary elaboration.

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?

Given the tool's moderate complexity (2 required parameters), no annotations, and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose, parameters, and data scope. However, for a read operation with no annotations, it could better address behavioral aspects like error handling or data freshness.

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?

Schema description coverage is 0%, so the schema provides no parameter documentation. The description compensates by explicitly listing both parameters (project_id and node_id) in the Args section, clarifying they are required identifiers. While it doesn't explain format constraints or provide examples, it successfully maps parameters to their purpose for node lookup.

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's purpose with a specific verb ('Get detailed information') and resource ('about a specific infrastructure node'). It distinguishes from sibling tools like 'get_nodes_overview' by focusing on a single node's comprehensive details rather than an overview. The bullet points provide concrete examples of what information is retrieved.

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?

The description implies usage context through the bullet points (e.g., retrieving metrics for monitoring), but doesn't explicitly state when to use this tool versus alternatives like 'get_nodes_overview' or 'get_project_status'. It mentions no prerequisites or exclusions, leaving the agent to infer appropriate scenarios based on the detailed nature of the information provided.

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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