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jamesbrink

MCP Server for Coroot

get_incident

Retrieve comprehensive incident details including timeline, affected applications, impact assessment, and resolution status from the Coroot observability platform.

Instructions

Get detailed information about a specific incident.

Retrieves comprehensive incident information including:

  • Timeline of events

  • Affected applications

  • Impact assessment

  • Resolution status

Args: project_id: Project ID incident_id: Incident ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
incident_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Core handler implementation for the get_incident MCP tool. Calls CorootClient.get_incident to fetch details and wraps in success response.
    async def get_incident_impl(project_id: str, incident_id: str) -> dict[str, Any]:
        """Get incident details."""
        incident = await get_client().get_incident(project_id, incident_id)
        return {
            "success": True,
            "incident": incident,
        }
  • MCP tool registration with @mcp.tool() decorator, including schema from parameters and docstring.
    @mcp.tool()
    async def get_incident(project_id: str, incident_id: str) -> dict[str, Any]:
        """Get detailed information about a specific incident.
    
        Retrieves comprehensive incident information including:
        - Timeline of events
        - Affected applications
        - Impact assessment
        - Resolution status
    
        Args:
            project_id: Project ID
            incident_id: Incident ID
        """
        return await get_incident_impl(project_id, incident_id)  # type: ignore[no-any-return]
  • CorootClient helper method that performs the actual HTTP API request to retrieve incident data from the Coroot server.
    async def get_incident(self, project_id: str, incident_id: str) -> dict[str, Any]:
        """Get detailed information about a specific incident.
    
        Args:
            project_id: Project ID.
            incident_id: Incident ID.
    
        Returns:
            Incident details including timeline and impact.
        """
        response = await self._request(
            "GET", f"/api/project/{project_id}/incident/{incident_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. It discloses that the tool retrieves comprehensive information and lists specific data categories (timeline, affected applications, impact assessment, resolution status), which adds useful context about what information is returned. However, it doesn't mention authentication requirements, rate limits, error conditions, or whether this is a read-only operation.

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 well-structured with a clear purpose statement, bulleted list of what's retrieved, and explicit parameter documentation. Every sentence earns its place, though the bulleted list could potentially be more concise.

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 that an output schema exists (so return values don't need explanation in the description), the description provides good context about what information is retrieved. For a read operation with 2 parameters, it's reasonably complete, though could benefit from more behavioral context given the lack of annotations.

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 descriptions. The description compensates by explicitly listing both parameters (project_id and incident_id) and clarifying they are IDs needed to identify the specific incident. This adds meaningful semantics beyond just the parameter names.

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 incident'). It distinguishes from sibling tools by focusing on incident retrieval rather than configuration, creation, deletion, or listing operations present in the sibling list.

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. While the description implies it's for retrieving detailed incident information, it doesn't specify prerequisites, when not to use it, or mention any alternative tools for similar purposes.

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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