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TradingView MCP

TradingView MCP

by madiver
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

data_get_pine_boxes

Reads box and zone boundaries drawn by Pine Script indicators and returns deduplicated high/low price zones, with study filtering to target a specific indicator.

Instructions

Read box/zone boundaries drawn by Pine Script indicators (box.new). Returns deduplicated {high, low} price zones. Use study_filter to target a specific indicator.

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": "data_get_pine_boxes"
  }
}

Input Schema

NameRequiredDescriptionDefault
verboseNoReturn all boxes with IDs and coordinates (default false — returns unique price zones)
study_filterNoSubstring to match study name. Omit for all.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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 states the operation is a read ('Read'), describes deduplication behavior, and specifies the returned data shape ('{high, low} price zones'). It could additionally mention edge cases like no matching boxes or sorting, but the essential safety and output traits are covered.

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?

Two sentences with no filler. The main action and output are stated first, followed by a concise parameter hint in the second sentence. Every phrase carries informational weight.

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?

The tool is simple: two optional parameters, no annotations, no output schema. The description gives the return type, the data source, and a filtering tip, which is sufficient for a basic read operation. It stops short of covering no-match behavior or the format of verbose output, but those are minor given the low complexity.

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 fully documents both 'verbose' and 'study_filter'. The description adds only a slight rephrasing of study_filter's purpose ('target a specific indicator') without introducing any meaning beyond what the schema provides, earning the baseline 3.

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 uses a specific verb ('Read'), a precise resource ('box/zone boundaries drawn by Pine Script indicators (box.new)'), and clearly states the output ('deduplicated {high, low} price zones'). It is instantly distinguishable from sibling tools like data_get_pine_lines, data_get_pine_labels, and data_get_pine_tables.

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

Usage Guidelines3/5

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

The description implies when to use this tool by naming the box/zone data source, which differentiates it from line/label/table readers. However, it does not explicitly mention alternatives or provide exclusion criteria, and the only guidance ('Use study_filter to target a specific indicator') is parameter-level rather than tool-selection-level.

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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