Skip to main content
Glama
Sign In
VTOP Bhopal MCP

VTOP Bhopal MCP

by divyarthjain
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_curriculum_progress

Read-onlyIdempotent

Fetches degree progress, including credits earned versus required, remaining credits, category and basket completion, CGPA, and grade counts to track graduation progress.

Instructions

Get degree progress: total credits earned vs required (and remaining), per-category breakdown (Foundation Core, Discipline Core, Discipline Electives, Open Electives, Projects/Internship, etc.), per-basket completion (HSM Elective, Foreign Language, Extra-curricular, ...), CGPA, and grade-letter counts across all semesters. Use this for any 'how many credits left?', 'how close am I to graduating?', 'which baskets do I still need?', or 'how many of each grade have I gotten?' questions. If the response contains NOT_AUTHENTICATED, immediately call get_captcha then login then retry this tool. login auto-uses VTOP_USERNAME/VTOP_PASSWORD env vars if set; if login replies that credentials are missing, ask the user for their VTOP username and password and call login again with them. Requires login.

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_curriculum_progress"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.5

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them by disclosing the authentication requirement, the exact NOT_AUTHENTICATED recovery chain (get_captcha → login → retry), and the VTOP_USERNAME/VTOP_PASSWORD env-var fallback. This is precisely the kind of operational context annotations cannot express.

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?

Purpose and return contents are front-loaded, and the sentences each carry information (scope, example questions, auth recovery). The auth narrative is somewhat long and slightly run-on, but nothing is 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?

With no output schema, the description carries the burden of return-value disclosure and does so by enumerating the reported sections (credits, categories, baskets, CGPA, grade counts). Combined with the auth-failure handling, an agent has everything needed to call and interpret this tool.

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, so the baseline of 4 applies and there is nothing param-level to disambiguate. The description correctly spends no space on inputs.

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?

Names a specific verb+resource (get degree progress) and enumerates exactly what is returned: credits earned vs required, per-category and per-basket breakdown, CGPA, and grade-letter counts. It is clearly distinguishable from siblings like get_curriculum_baskets or get_pending_subjects, which cover narrower slices.

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?

Gives concrete user-question triggers ('how many credits left?', 'how close am I to graduating?', 'which baskets do I still need?') that make the intended use unambiguous. It does not name an alternative tool or state when NOT to use it, so it falls short of full when/when-not routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools