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New Relic MCP Server

by piekstra

list_deployments

Retrieve deployment history for a New Relic application to track changes and monitor release cycles.

Instructions

List deployments for an application

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main MCP tool handler and registration for 'list_deployments'. This function is decorated with @mcp.tool() and implements the tool logic by calling the NewRelicClient's list_deployments method and returning JSON.
    @mcp.tool()
    async def list_deployments(app_id: str) -> str:
        """List deployments for an application"""
        if not client:
            return json.dumps({"error": "New Relic client not initialized"})
    
        try:
            result = await client.list_deployments(app_id)
            return json.dumps(result, indent=2)
        except Exception as e:
            return json.dumps({"error": str(e)}, indent=2)
  • Helper method in NewRelicClient class that performs the actual API request to fetch deployments for a given application ID.
    async def list_deployments(self, app_id: str) -> Dict[str, Any]:
        """List deployments for an application"""
        url = f"{self.base_url}/applications/{app_id}/deployments.json"
        return await self._make_request("GET", url)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states a read operation ('List'), implying it's non-destructive, but doesn't cover critical aspects like pagination, rate limits, authentication needs, or error handling. For a tool with no annotations, this is a significant gap in transparency.

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 a single, clear sentence with zero waste—it directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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 low complexity (1 parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete parameter semantics, it lacks depth for safe and effective use, such as missing behavioral context or usage guidelines.

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?

The input schema has 1 parameter (app_id) with 0% description coverage, so the schema provides no semantic context. The description mentions 'for an application', which loosely relates to app_id but doesn't explain its format, constraints, or where to obtain it. This adds minimal value beyond the schema, aligning with the baseline for low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List deployments for an application' clearly states the verb ('List') and resource ('deployments'), making the purpose understandable. However, it lacks specificity about scope (e.g., all deployments vs. recent ones) and doesn't distinguish from sibling tools like 'list_applications' or 'create_deployment', which would require more detail to reach higher scores.

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 prerequisites (e.g., needing an app_id), exclusions, or comparisons to siblings like 'list_applications' for broader context. This leaves the agent without clear usage instructions beyond the basic function.

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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