VTOP Bhopal MCP

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get_captcha

Fetches the VTOP CAPTCHA image for login so the assistant can OCR it and immediately call login with the text, without asking the user to read it.

Instructions

Step 1 of login: fetch a CAPTCHA image from VTOP. Returns the image so you (the model) can OCR it. After this, immediately call login with the captcha text you read — do NOT ask the user to read it for you. The user only needs to be asked for credentials if VTOP_USERNAME / VTOP_PASSWORD are not set as env vars on the server.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_captcha"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.5Oct 17, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations cover the safety profile (destructiveHint=false, openWorldHint=true), so the bar is lower, yet the description adds real behavioral context: it returns an image intended for the model to OCR, and it discloses the credential/env-var dependency. It stops short of describing failure modes (e.g., what happens if OCR fails or the captcha expires), which a login-flow tool could reasonably include.

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?

Three sentences, front-loaded with the 'Step 1 of login' frame, and each sentence carries actionable instruction (what it returns, what to do next, when to involve the user). No filler.

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?

No output schema exists, and the description compensates by explaining the return value (an image for OCR) and the downstream handoff to `login`. For a parameterless, single-step tool this is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters and the schema is empty, so there is nothing to disambiguate; baseline for 0 params is 4. No misleading parameter guidance is present.

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?

States a specific verb (fetch) and resource (CAPTCHA image from VTOP), and frames it as 'Step 1 of login'. It distinguishes itself from the large sibling list (get_marks, login, etc.) by naming `login` as the required follow-up, so an agent knows exactly where this fits in the flow.

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

Usage Guidelines5/5

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

Explicit when-to-use (step 1 of login), what to do immediately after (call `login` with the OCR'd text), and a clear negative instruction (do NOT ask the user to read the captcha). It even scopes when user credentials are needed. Nothing is left to inference.

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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