MCP Yahoo Finance

get_news

Fetch normalized news articles for a stock symbol, with optional date range and article limit, to support financial research.

Instructions

Get normalized, bounded news for a stock symbol.

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": {
      "symbol": "<symbol>"
    },
    "name": "get_news"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Maximum number of articles, from 1 to 100.
`symbol`	Yes	Stock symbol in Yahoo Finance format.
`end_date`	No	Include articles published on or before this YYYY-MM-DD date.
`start_date`	No	Include articles published on or after this YYYY-MM-DD date.

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.2.0Oct 1, 2026

addedInput schema / properties / end_date

Added value: +{
+  "default": null,
+  "description": "Include articles published on or before this YYYY-MM-DD date.",
+  "type": "string"
+}

addedInput schema / properties / limit

Added value: +{
+  "default": 10,
+  "description": "Maximum number of articles, from 1 to 100.",
+  "type": "integer"
+}

addedInput schema / properties / start_date

Added value: +{
+  "default": null,
+  "description": "Include articles published on or after this YYYY-MM-DD date.",
+  "type": "string"
+}

First observedv1.0.0Aug 18, 2025

TDQS

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It adds only 'normalized, bounded' (the latter partly duplicates the schema's limit) and does not disclose read-only status, data source, rate limits, or return format.

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; every word contributes to the tool's core purpose.

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?

Minimum viable: the schema fully documents the parameters, so an agent can invoke it, but with no annotations and no output schema the description does not explain return shape or normalization details. It leaves meaningful behavioral context unstated.

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 documents symbol, limit, start_date, and end_date. The description adds 'for a stock symbol' but no additional parameter syntax, defaults, or constraints beyond the schema.

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 ('Get') and resource ('news') scoped to a stock symbol, clearly distinct from the many price and financial-statement siblings. However, 'normalized, bounded' are vague qualifiers and it does not explicitly name what it is not.

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?

Provides no when-to-use, when-not-to-use, or alternative-tool guidance among the many sibling data tools. Usage is only inferable 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.