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jackdark425

Financial Modeling Prep (FMP) MCP Server

by jackdark425

get_stock_news

Retrieve news articles for a specific stock ticker symbol to analyze market sentiment and stay informed about company developments.

Instructions

Get latest news articles for a stock symbol

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock ticker symbol
limitNoNumber of articles to return (default: 10)

Implementation Reference

  • Implementation of the get_stock_news tool handler in src/tools/financials.ts.
    server.registerTool(
      'get_stock_news',
      {
        description: 'Get latest news articles for a stock symbol',
        inputSchema: StockNewsSchema,
      },
      async (args: z.infer<typeof StockNewsSchema>) => {
        try {
          const limit = args.limit || 10;
          const data = await fetchFMP(`/news/stock?symbols=${args.symbol.toUpperCase()}&limit=${limit}`);
          return jsonResponse(data);
        } catch (error) {
          return errorResponse(error);
        }
      }
    );
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'latest news articles' but doesn't specify source, freshness, format, pagination, rate limits, or authentication requirements. For a read operation with external data, this lack of context is a significant gap.

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 a single, efficient sentence that directly states the tool's function without any fluff. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the return values look like (e.g., article titles, dates, sources), potential errors, or behavioral constraints. For a tool fetching dynamic external data, this leaves critical gaps for the agent.

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%, with clear parameter documentation in the schema. The description adds no additional meaning beyond implying news retrieval for a stock symbol, which the schema already covers with the 'symbol' parameter. This meets the baseline for high schema coverage.

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 clearly states the tool's purpose: 'Get latest news articles for a stock symbol.' It specifies the action (get) and resource (news articles) with the target (stock symbol). However, it doesn't differentiate from sibling tools like 'search_symbol' or 'get_company_profile' that might also provide news-related information, preventing a score of 5.

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 provides no guidance on when to use this tool versus alternatives. With siblings like 'search_symbol' and 'get_company_profile' that might overlap in functionality, there's no indication of context, prerequisites, or exclusions. This leaves the agent guessing about the best tool selection.

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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