massive-mcp

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get_rsi

Calculates the Relative Strength Index (RSI) for a stock ticker using a configurable period (default 14) to identify overbought or oversold conditions.

Instructions

Relative Strength Index values for a stock. Default window 14.

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": {
      "ticker": "<ticker>"
    },
    "name": "get_rsi"
  }
}

Input Schema

Name	Required	Default
`ticker`	Yes
`timespan`	No	day
`window`	No
`series_type`	No	close
`timestamp`	No
`limit`	No
`cursor`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 8, 2026

TDQS

C2.8/5.0

Behavior2/5

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

No annotations exist; the description only notes the default window but fails to disclose behavioral traits such as rate limits, pagination (cursor), or data freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (two sentences) and front-loaded with the core purpose. However, the second sentence about default window is somewhat redundant with the schema.

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?

Although an output schema exists, the description is too sparse for a 7-parameter technical indicator tool. It lacks context about parameter combinations, usage patterns, and return value summary.

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

Parameters1/5

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

Schema description coverage is 0%, and the description only mentions the default window. It does not explain ticker, timespan, series_type, timestamp, limit, or cursor parameters, leaving the AI agent underinformed.

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 tool calculates 'Relative Strength Index values for a stock' and mentions the default window. This distinguishes it from siblings like get_ema or get_sma.

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 on when to use this tool versus alternatives, no context provided, and no mentions of prerequisites or exclusions.

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