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sandraschi

Windows Operations MCP

by sandraschi

agentic_system_hardening

Audit Windows services, registry, or accounts for security gaps and apply high-priority fixes automatically. Choose dry-run for recommendations or live mode for immediate hardening.

Instructions

Autonomous Windows security hardening with SEP-1577 sampling.

Phases: (1) Inventory the target subsystem, (2) LLM audit for hardening recommendations, (3) Apply HIGH-priority fixes in live mode.

Return Format

{
  "success": bool,
  "target": str,
  "dry_run": bool,
  "audit_recommendations": str,
  "actions_taken": [{"action": str, "status": str}]
}

Examples

agentic_system_hardening(target="services", dry_run=True)
agentic_system_hardening(target="accounts", dry_run=False)

Notes:

  • ctx is required; returns error if called without it.

  • dry_run=False will queue up to 5 HIGH-priority actions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesSubsystem to harden.
dry_runNoAudit only (True) or apply fixes (False).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv15.3.0
    • addedInput schema / properties / dry_run / description
      Added value: +"Audit only (True) or apply fixes (False)."
    • addedInput schema / properties / target / description
      Added value: +"Subsystem to harden."
  2. First observedv14.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations provide no hints (all false), so the description carries the burden. It discloses that dry_run=False will apply HIGH-priority fixes and queue up to 5 actions, indicating potentially destructive behavior. It also notes ctx is required and shows the return format, adding transparency beyond the annotations.

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 with a clear lead sentence, phased breakdown, return format block, examples, and notes. It is concise and front-loaded, containing only essential information without fluff.

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

Completeness5/5

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

Given the tool's complexity (multi-phase autonomous hardening), the description covers the workflow, return format, examples, and key notes about dry_run behavior and context requirements. It provides enough context for an agent to decide when and how to call it, and the output format is explicitly shown.

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 already provides descriptions for both parameters (target enum and dry_run boolean), with 100% coverage. The description adds examples and notes about ctx, but does not significantly expand on parameter semantics beyond the schema.

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 performs autonomous Windows security hardening with SEP-1577 sampling, and outlines three phases (inventory, audit, apply fixes). This differentiates it from the many granular winops_* sibling tools by presenting a higher-level, multi-step operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear sense of when to use it (for autonomous hardening) and includes details on dry_run vs. live mode, plus a note about requiring ctx. It does not explicitly mention when not to use it or alternatives, but the phased workflow and examples imply its purpose and appropriate invocation context.

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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