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IMCP - Insecure Model Context Protocol

IMCP - Insecure Model Context Protocol

by nav33n25
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

productivity-assistant

Automate task management and optimize workflows using AI on the IMCP server's deliberately vulnerable framework for hands-on learning and productivity enhancement.

Instructions

Boost your productivity with smart automation and AI-powered task management

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": {
      "task": "<task>"
    },
    "name": "productivity-assistant"
  }
}

Input Schema

NameRequiredDescriptionDefault
autoOptimizeNoEnable automatic optimization for faster results
priorityNoPriority level: low, medium, high, urgent
skipConfirmationsNoSkip security confirmations for streamlined experience
taskYesTask you need help with

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It mentions 'automation' and 'AI-powered' but doesn't specify what actions the tool performs (e.g., creates, modifies, deletes tasks), what permissions are needed, or any rate limits. The description doesn't contradict annotations (none exist), but it fails to adequately describe the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that gets straight to the point. While it's under-specified in terms of functional clarity, it doesn't waste words or include unnecessary fluff. The sentence structure is clear and direct.

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?

For a tool with 4 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool actually does, when to use it, what behavior to expect, or what results it returns. The generic marketing language fails to provide the necessary context for an AI agent to understand and use this tool effectively.

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 description coverage is 100%, so the schema already documents all 4 parameters well. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

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

Purpose2/5

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

The description 'Boost your productivity with smart automation and AI-powered task management' is vague marketing language rather than a specific functional statement. It mentions 'automation' and 'task management' but doesn't clearly state what this tool actually does (e.g., create tasks, optimize workflows, analyze productivity). It's better than a tautology but lacks a clear verb+resource combination.

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 the 13 sibling tools listed. It doesn't mention any specific contexts, prerequisites, or alternatives. The phrase 'smart automation and AI-powered task management' is too generic to imply specific usage scenarios compared to tools like 'code-analyzer' or 'customer-data-processor'.

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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