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tradingview-mcp

tradingview-mcp

by GlynnCarson
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

smart_volume_scanner

Read-only

Scan markets for volume spikes combined with technical analysis filters like RSI and price change to identify trading opportunities.

Instructions

Smart volume + technical analysis combination scanner.

Args: exchange: Exchange name min_volume_ratio: Minimum volume multiplier (default 2.0) min_price_change: Minimum price change percentage (default 2.0) rsi_range: "oversold" (<30), "overbought" (>70), "neutral" (30-70), "any" limit: Number of results (max 30)

Returns list[dict] on success. On ANY failure returns a structured error envelope {"error": {"code": ..., "retryable": ...}}.

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": "smart_volume_scanner"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
exchangeNoKUCOIN
rsi_rangeNoany
min_price_changeNo
min_volume_ratioNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.1

TDQS

A3.8/5.0
Behavior4/5

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

Beyond the readOnlyHint and non-destructive annotations, the description explicitly reveals the success return type (list[dict]) and the failure envelope with retryable flag. It also notes a max result limit of 30. This provides meaningful runtime behavior that annotations alone would not convey.

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 structured into a one-sentence summary, a parameter list, and a return/error statement. Every line adds necessary information and nothing is repeated. It is an appropriate length for a 5-parameter tool.

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?

For a read-only scanner with all-optional parameters, the description covers the return contract, error shape, and all parameter semantics. No critical information about how to invoke or interpret the result is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden of explaining parameters. It does so for all 5 parameters, including valid rsi_range values, defaults for min_volume_ratio and min_price_change, and a max for limit. It is slightly terse for exchange but sufficient.

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 states a clear combination scanner purpose: it combines volume and technical analysis. It doesn't use a verb like 'scan' or 'screen,' but the noun phrase is specific and suggests what the tool does. It distinguishes itself from pure volume and pure technical scanners, though not by name.

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?

The description gives no explicit when-to-use guidance or exclusions, and it never references siblings such as volume_breakout_scanner or bollinger_scan. The presence of filters implies its use case, but the agent is left to infer when to select it over alternatives.

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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