QUOTEZ

Overview Schema Source Related Servers Score Discussions Admin

Get account state

get_account

Read-only

Retrieve a connected account's balance, equity, margin, and leverage while protecting privacy by masking the login to its last four digits.

Instructions

Return the connected account's balance, equity, margin and leverage.

The login is masked to its last four digits and the broker, server and account holder names are never returned. On the replay source these figures are invented placeholders describing no real account: the payload carries synthetic=true, the currency is SYN and the login is ****0000. Do not restate them as a real balance.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`equity`	Yes	Balance plus floating profit and loss.
`margin`	Yes	Margin currently in use.
`source`	Yes	Data source that produced these figures.
`balance`	Yes	Balance, excluding floating profit and loss.
`currency`	Yes	Account deposit currency.
`leverage`	Yes	Account leverage, for example 100 for 1:100.
`synthetic`	Yes	True when the figures are generated. The replay source always sets this, and its balance and equity are invented placeholders that describe no real account.
`margin_free`	Yes	Margin available for new positions.
`login_masked`	Yes	Account login masked to its last four digits. The full login is never returned.
`margin_level`	Yes	Equity divided by margin, as a percentage.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 19, 2026

TDQS

A4.5/5.0

Behavior5/5

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

The description discloses key behavioral traits beyond annotations: login masking, omission of broker/server/account holder names, and synthetic data indicators on replay. This adds significant value over the readOnlyHint and openWorldHint annotations.

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 three sentences long, front-loaded with the main purpose, and every sentence adds essential information. There is no redundancy or wasted language.

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 tool has no parameters and an output schema exists, the description adequately covers the return values and adds critical context about data masking and synthetic mode. It is complete for an agent to understand and invoke the tool correctly.

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?

The tool has no parameters and schema coverage is 100%, so the baseline is 3. The description does not add meaning to any parameters because there are none to explain; it appropriately focuses on the tool's output and behavior.

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 clearly states the verb 'Return' and the specific resource 'connected account's balance, equity, margin and leverage'. This distinguishes it from sibling tools like list_symbols, get_quote, and get_bars, which operate on different data.

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 provides clear context about when the tool returns synthetic data on the replay source and warns against restating it as real. It does not explicitly contrast with siblings, but the context is sufficient for an agent to understand when to use this tool.

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

Install Server