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sheypoor-mcp

sheypoor-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Daily car prices

sp_car_prices
Read-onlyIdempotent

Retrieve daily car market and factory prices by model and year, including today's percentage change, to compare a car's price with market averages (quotes, not ads).

Instructions

Get Sheypoor's daily car price list (قیمت روز خودرو): market price and factory price per model and year, with the day's change.

Use it to check a car's price against the market average (quotes, not ads). market is the open-market price, factory the maker's list price. Toman; change_pct is today's market move. For ad prices use sp_price_summary.

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": "sp_car_prices"
  }
}

Input Schema

NameRequiredDescriptionDefault
yearNoModel year, e.g. 1404.
groupNoMaker group. Omit for all.
limitNoMax models.
queryNoBrand or model words, Persian or English, e.g. پراید, 206.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely new context: the data is quotes not ads, values are in Toman, and change_pct is today's market move. It says nothing about how limit interacts with result volume or how the daily snapshot is refreshed, so with annotations carrying most of the burden a 3 is appropriate.

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 purpose and usage are front-loaded in the first two sentences, and the field glossary is short and scannable. There is mild redundancy between 'market price and factory price per model and year' and the later re-definition of market and factory, which costs it the top mark.

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?

With no output schema, the description usefully explains the returned fields and currency, which is the main thing an agent would otherwise lack. It does not cover result-volume expectations or how a null year/group behaves beyond 'Omit for all', but nothing essential to calling the tool correctly is missing.

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% and each parameter already has inline documentation including examples, so this is the baseline case. The description's added detail (market vs factory, Toman, change_pct) describes return fields rather than clarifying the year, group, limit or query inputs 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 states a specific verb and resource ('Get Sheypoor's daily car price list') plus scope ('market price and factory price per model and year, with the day's change'), and it explicitly distinguishes the dataset as quotes rather than ads, which separates it from the ad-oriented siblings.

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?

It gives a concrete use case ('check a car's price against the market average') and names the alternative for the other case ('For ad prices use sp_price_summary'), so the routing decision is explicit rather than inferred.

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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