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yfinance-ai MCP server

yfinance-ai MCP server

by lkcair
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_sector_performance

Read-onlyIdempotent

Retrieve performance data for major S&P 500 sectors to analyze market trends and compare sector returns.

Instructions

Get performance of major market sectors.

Returns: Performance data for major S&P 500 sectors

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": "get_sector_performance"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so the safety and mutability profile is fully covered. The description adds only the S&P 500 scoping detail; it says nothing about the timeframe of the performance data, so it is marginally useful beyond structured fields.

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?

Two short sentences, front-loaded with the purpose. The 'Returns:' line partially duplicates the purpose statement, but with an output schema present it is not wasteful enough to penalize heavily.

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

Completeness3/5

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

For a zero-parameter tool with rich annotations and an output schema, the description is close to adequate, and return values need not be explained. The remaining gap is selection context: it never clarifies how it differs from get_sector_overview or what period the performance covers.

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?

The tool takes zero parameters, so the schema offers nothing to explain and the baseline of 4 applies. There are no parameter concepts the description could meaningfully add.

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 clear verb and resource ('Get performance of major market sectors') and narrows scope to S&P 500 sectors, which is more specific than a bare title. However, it does not distinguish itself from the very similar sibling get_sector_overview, leaving an agent unsure which sector tool to pick.

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 when-to-use guidance is provided, and the near-identical sibling get_sector_overview is never mentioned as an alternative. The agent must infer the use case purely from the resource name.

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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