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TradingView Unified MCP

TradingView Unified MCP

by daviddme
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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indicator_get_inputs

Read-only

Read all input IDs, values, and display names for one exact TradingView study. Use it to inspect indicator input settings before changing them.

Instructions

Read all input IDs, values and available display names for one exact study.

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": {
      "entity_id": "<entity_id>"
    },
    "name": "indicator_get_inputs"
  }
}

Input Schema

NameRequiredDescriptionDefault
entity_idYesExact registered study ID
target_idNoExact Chrome tab target ID from browser_list_tabs. Required for changes.
expected_layout_idNoExpected saved-layout ID. A mismatch stops the operation before writing.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, lowering the bar. The description adds what is returned (IDs, values, display names), but says nothing about missing display names, output size, or why the write-oriented target_id/expected_layout_id parameters exist on a read tool.

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?

A single front-loaded sentence with no filler; the verb, scope, and result contents are all stated up front.

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?

For a read-only tool with full annotation coverage, a documented schema, and no output schema, the description is largely sufficient — it even names the returned fields. The only real gap is not clarifying that target_id/expected_layout_id are irrelevant to this read path.

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 coverage is 100%, so baseline is 3. 'One exact study' reinforces that entity_id must be a single exact ID, but the description adds no semantics for target_id or expected_layout_id, which the schema frames as change-related and are confusing on a read-only call.

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?

States a specific verb (read) and resource (input IDs, values, display names) scoped to 'one exact study'. An agent can distinguish it from indicator_set_inputs and indicator_list without opening a schema, though it never names those siblings explicitly.

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?

'For one exact study' implies the usage context, but there is no explicit when-to-use, when-not, or pointer to alternatives (indicator_list, strategy_get_inputs, data_get_study_values). Guidance is implied rather than stated.

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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