QuantXData MCP Server

get_orderbooks

Retrieve historical order book snapshots (L1 top-of-book or L2 depth) for any exchange and trading pair, with options for start time and result limit.

Instructions

Get historical order book snapshots (L1 top-of-book or L2 depth)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "exchange": "<exchange>",
      "instrument": "<instrument>"
    },
    "name": "get_orderbooks"
  }
}

Input Schema

Name	Required	Description
`from`	No	Start timestamp (ISO 8601)
`limit`	No	Max results (default: 100)
`exchange`	Yes	Exchange name
`instrument`	Yes	Trading pair

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 2, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'historical' and 'snapshots' but fails to describe return format, pagination, ordering, or any side effects. The L1/L2 distinction is vague and does not clarify how it impacts results.

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 a single sentence that is concise and to the point. It communicates the core purpose without any unnecessary words or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is relatively simple with 4 parameters and no output schema, but the description omits critical details such as the response structure, default limit behavior, and how L1 vs L2 depth is determined. This is inadequate for an AI agent to understand the full behavior without exploring further.

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 schemas for all 4 parameters have descriptions with 100% coverage, so the schema already explains the parameters. The description adds context about the data type (historical snapshots) but does not enhance parameter understanding beyond what is already in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves historical order book snapshots with L1 or L2 depth, but it doesn't explicitly differentiate from sibling tools like get_ob_l1_top or get_ob_l2_snapshot. The verb 'Get' and resource are clear, but the scope could be more distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. It merely states it gets historical data, which implies a contrast with real-time tools, but this is not explicit. There is no mention of when to prefer this over get_ob_l1_top or get_ob_l2_snapshot.

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

Deploy Server