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SDLC Command Center MCP Server

SDLC Command Center MCP Server

by Senpai-Sama7
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Rollback Change Set (Gated)

sdlc_rollback
Destructive

Roll back changes from a recorded change set by restoring modified files or deleting created ones. Dry-run by default; confirm=true to execute.

Instructions

Restore files from a recorded change set (or delete files it created). Dry-run unless confirm=true; the rollback itself is audited.

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": {
      "changeId": "<changeId>"
    },
    "name": "sdlc_rollback"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathNoTarget directory. Filesystem roots are rejected; UNC/network paths require an explicit environment override.
dryRunNoExplicit dry-run switch. Mutation only occurs when dryRun is false AND confirm is true.
confirmNoApproval gate. Without confirm=true the call is a dry-run and changes nothing.
changeIdYesIdentifier returned by a write operation.

Output Schema

NameRequiredDescriptionDefault
planNo
statusNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate destructiveHint=true. The description adds beyond by specifying the dry-run gate ('Dry-run unless confirm=true') and that the rollback is audited. This provides valuable behavioral context beyond the annotation alone.

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, front-loaded sentence that efficiently conveys purpose, behavior, and key constraint. Every word earns its place; no filler.

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?

With an output schema present, return details are covered elsewhere. The description adequately explains the core action, the dry-run gating, and the audit trail. Minor gaps (e.g., behavior when changeId is invalid) but overall complete for the tool's complexity.

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 coverage is 100% with parameter descriptions. The description adds overall context about dry-run and confirm interaction, but does not detail each parameter further. Baseline 3 is appropriate as the schema already does the heavy lifting.

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 phrase 'Restore files from a recorded change set (or delete files it created)' clearly states the action and resource. It distinguishes from write/read siblings by focusing on reverting changes. The dry-run and audit details add specificity.

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 for rolling back changes with a dry-run by default, but does not explicitly say when to avoid or compare to alternatives like sdlc_write_file. The condition for mutation (confirm=true) is stated but not contextualized against other tools.

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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