ESA MCP Server

deployment_delete

Remove a specific code version from an Edge Routine deployment to manage your edge computing resources and maintain clean version control.

Instructions

Delete a specified code version associated with an Edge Routine (ER).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>",
      "codeVersion": "<codeVersion>"
    },
    "name": "deployment_delete"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes	The name of the deployment to delete
`codeVersion`	Yes	The version of the code to delete

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 18, 2025

TDQS

C2.9/5.0

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 the tool deletes a code version, implying a destructive operation, but does not mention critical details like permissions required, whether the deletion is reversible, side effects on associated resources, or error handling. This is inadequate for a mutation tool.

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, direct sentence that efficiently conveys the core action without unnecessary words. It is front-loaded with the verb 'Delete' and specifies the resource clearly, making it easy to parse and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's destructive nature, lack of annotations, and no output schema, the description is insufficient. It does not cover behavioral aspects like safety warnings, return values, or error conditions, leaving significant gaps for an AI agent to use it correctly in context.

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 100% description coverage, clearly documenting both parameters ('name' and 'codeVersion'). The description does not add any semantic details beyond what the schema provides, such as format examples or constraints, so it meets the baseline score for high schema coverage.

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 ('Delete') and the target ('a specified code version associated with an Edge Routine (ER)'), making the purpose unambiguous. However, it does not explicitly differentiate this tool from sibling tools like 'routine_delete' or 'delete_record', which could handle similar deletion operations in different contexts.

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, such as 'routine_delete' for deleting entire routines or 'delete_record' for other record types. It lacks context about prerequisites, dependencies, or scenarios where this deletion is appropriate, leaving usage unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.