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sheypoor-mcp

sheypoor-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Price summary for a search

sp_price_summary
Read-onlyIdempotent

Summarizes asking prices from the newest Sheypoor ads for a search, returning count, min, median, quartiles, max, and cheapest/priciest listings so you can answer “what does X cost?”

Instructions

Summarise asking prices of the newest ads for a search: count, min, median, quartiles, max, plus cheapest and priciest ads.

Use it for "what does X cost on Sheypoor": asking prices of the newest ads, not sold prices. Ads without a numeric price and prices under 10,000 Toman are left out. Narrow the query (year, brand, city) for a useful median. Values are in Toman.

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_price_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
cityNoCity or province slug from sp_cities, e.g. tehran. 'iran' = all Iran.iran
pagesNoResult pages (24 ads each) to sample.
queryNoPersian words, e.g. پراید.
filtersNoFilters from sp_filters as {name: value}: a<id> option id, mn<id>/mx<id> range ends (mn68101: '1400' = year from).
categoryNoSlug from sp_categories (car, mobile-phone) or sp_filters path (car/peugeot/206). Omit for all.
max_priceNoHighest price, Toman.
min_priceNoLowest price, Toman.
neighbourhoodsNoNeighbourhood ids from sp_filters(area=...), e.g. ['888']. City-level only.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the supplied annotations (readOnly, idempotent, non-destructive), the description discloses important behavioral details: it samples the newest ads, excludes ads without a numeric price, ignores prices under 10,000 Toman, reports values in Toman, and warns that narrowing the query improves the median. These are substantive operational traits an agent needs before calling it.

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 is front-loaded with the core summary contents, followed by usage context and important caveats in a compact two-paragraph structure. No sentence is wasted; each adds useful information.

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?

For a tool with eight optional parameters and no output schema, the description fully covers what the tool returns (statistics and example ads), what is excluded, the unit of currency, and how sampling works. An agent has enough context to call it correctly and interpret the result.

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 every parameter is already documented in the input schema. The description adds only a general hint to narrow the query by year, brand, or city, which is marginal given the schema's detailed field descriptions.

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: 'Summarise asking prices of the newest ads for a search: count, min, median, quartiles, max, plus cheapest and priciest ads.' It clearly distinguishes this aggregation tool from sibling ad-listing tools like sp_search or sp_ad, and the stated output components make the purpose unambiguous.

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?

It gives explicit when-to-use guidance ('what does X cost on Sheypoor') and a key restriction ('asking prices of the newest ads, not sold prices'), plus advice to narrow the query for a useful median. However, it does not explicitly name alternatives such as sp_car_prices or sp_area_prices, leaving the agent to infer when those siblings are preferable.

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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