market-mcp

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get_quote

Read-onlyIdempotent

Retrieve current market data for any security: price, daily change percent, volume, and trading status, from real-time or delayed exchange data.

Instructions

Текущая котировка бумаги: цена, изменение за день в %, объём, статус торгов.

    Источник — T-Invest в реальном времени (если задан токен), иначе MOEX ISS с задержкой 15 минут
    (stale: true). Вне торгов price — цена закрытия, в ответе notice.code = market_closed.
    Для облигаций price — рублёвая цена одной бумаги с НКД, price_pct_of_face — цена в % от номинала.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`board`	No	Режим торгов (class code): TQBR, TQCB, TQOB, TQTF, CETS, SPBFUT. Нужен только если тикер неоднозначен.
`ticker`	Yes	Тикер или SECID: SBER, SU26238RMFS4, CNYRUB_TOM, IMOEX.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 17, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Beyond the read-only annotation, the description discloses fallback data sources, the stale flag, market-closed notice codes, and bond price semantics with NKD. This gives an agent important behavioral expectations that annotations alone do not cover.

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 first sentence front-loads the core purpose and result fields, then subsequent sentences add only high-value behavioral context: source, staleness, after-hours behavior, and bond pricing. Every sentence earns its place.

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?

Given the output schema exists and read-only annotations are present, the description covers the key invocation contexts: real-time vs delayed, stale data, market-closed behavior, and bond-specific price interpretation. An agent has enough to call the tool correctly in normal and edge cases.

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 ticker and board adequately. The description adds no new parameter-level meaning; its extra details are mostly about output behavior, so baseline 3 is appropriate.

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 resource ('котировка бумаги') and the exact data returned: price, daily change percent, volume, and trading status. This clearly distinguishes it from siblings like get_candles or get_orderbook even without naming them.

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?

The description gives clear context: real-time T-Invest when a token is set, otherwise 15-minute delayed MOEX ISS data, and after-hours behavior. It does not explicitly name alternative sibling tools or state when not to use this tool, so it stops short of a 5.

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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