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Damn Vulnerable MCP Server (DVMCP)

Damn Vulnerable MCP Server (DVMCP)

by Kyze-Labs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

support.reply_to_ticket

Reply to a customer support ticket to resolve it; the reply is sent to the customer's email and the ticket is marked as resolved.

Instructions

Send a reply to a customer support ticket. The reply is sent to the customer's email and the ticket is marked as resolved.

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": {
      "ticket_id": "<ticket_id>",
      "message": "<message>"
    },
    "name": "support.reply_to_ticket"
  }
}

Input Schema

NameRequiredDescriptionDefault
ticket_idYesTicket ID to reply to
messageYesReply message content

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It explicitly states that the reply goes to the customer's email and that the ticket is marked as resolved, which is a non-obvious side effect. However, it does not cover other possible behavioral aspects like reversibility or error handling.

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 consists of two concise sentences that front-load the main action and then provide the key side effect. There is no filler or redundant information, making it highly efficient.

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?

For a simple 2-parameter tool with no output schema and no annotations, the description covers the core behavior and the important side effect of marking the ticket resolved. It is adequate, though it lacks potential caveats such as whether the ticket must be open or if the action is permanent.

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 ('Reply message content' and 'Ticket ID to reply to'), and the description adds no additional parameter meaning. With 100% schema coverage, the baseline score of 3 is appropriate.

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 identifies the tool's function with a specific verb ('Send') and resource ('customer support ticket'), and it distinguishes itself from sibling tools by noting the reply is sent to the customer's email and the ticket is marked as resolved. This makes the purpose unambiguous and well-differentiated.

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 provides clear context for when to use the tool: to send a reply and resolve a ticket. It does not explicitly mention alternative tools or exclusions, but the context is sufficient for basic selection among related support tools like read_tickets or search_knowledge_base.

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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