Skip to main content
Glama
matteoantoci

Marketstack MCP Server

by matteoantoci

get_dividends_data

Retrieve detailed stock dividend data for specific symbols using the Marketstack MCP Server. Filter by date range, sort order, and pagination to access historical or current dividend information efficiently.

Instructions

Look up information about the stock dividend for different symbols.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
date_fromNoFilter results based on a specific timeframe by passing a from-date in `YYYY-MM-DD` format. You can also specify an exact time in ISO-8601 date format, e.g. `2020-05-21T00:00:00+0000`.
date_toNoFilter results based on a specific timeframe by passing an end-date in `YYYY-MM-DD` format. You can also specify an exact time in ISO-8601 date format, e.g. `2020-05-21T00:00:00+0000`.
limitNoSpecify a pagination limit (number of results per page) for your API request. Default limit value is `100`, maximum allowed limit value is `1000`.
offsetNoSpecify a pagination offset value for your API request. Example: An offset value of `100` combined with a limit value of 10 would show results 100-110. Default value is `0`, starting with the first available result.
sortNoBy default, results are sorted by date/time descending. Use this parameter to specify a sorting order. Available values: `DESC` (Default), `ASC`.DESC
symbolsYesSpecify one or multiple comma-separated stock symbols (tickers) for your request, e.g. `AAPL` or `AAPL,MSFT`. Each symbol consumes one API request. Maximum: 100 symbols

Implementation Reference

  • The main handler function that executes the tool logic by constructing API parameters and calling the Marketstack client to fetch dividends data.
    const getDividendsDataHandler = async (input: Input, client: MarketstackClient): Promise<Output> => {
      try {
        const { symbols, sort, date_from, date_to, limit, offset } = input;
    
        const apiRequestParams: MarketstackApiParams = {
          endpoint: 'dividends',
          symbols,
          ...(sort && { sort }), // Include if sort is provided
          ...(date_from && { date_from }), // Include if date_from is provided
          ...(date_to && { date_to }), // Include if date_to is provided
          ...(limit && { limit }), // Include if limit is provided
          ...(offset && { offset }), // Include if offset is provided
        };
    
        const data = await client.fetchApiData(apiRequestParams);
    
        return data;
      } catch (error: unknown) {
        console.error('getDividendsData tool error:', error);
        const message = error instanceof Error ? error.message : 'An unknown error occurred.';
        throw new Error(`getDividendsData tool failed: ${message}`);
      }
    };
  • Zod schema defining the input parameters for the get_dividends_data tool.
    const getDividendsDataInputSchemaShape = {
      symbols: z
        .string()
        .describe(
          'Specify one or multiple comma-separated stock symbols (tickers) for your request, e.g. `AAPL` or `AAPL,MSFT`. Each symbol consumes one API request. Maximum: 100 symbols'
        ),
      sort: z
        .enum(['DESC', 'ASC'])
        .optional()
        .default('DESC')
        .describe(
          'By default, results are sorted by date/time descending. Use this parameter to specify a sorting order. Available values: `DESC` (Default), `ASC`.'
        ),
      date_from: z
        .string()
        .optional()
        .describe(
          'Filter results based on a specific timeframe by passing a from-date in `YYYY-MM-DD` format. You can also specify an exact time in ISO-8601 date format, e.g. `2020-05-21T00:00:00+0000`.'
        ),
      date_to: z
        .string()
        .optional()
        .describe(
          'Filter results based on a specific timeframe by passing an end-date in `YYYY-MM-DD` format. You can also specify an exact time in ISO-8601 date format, e.g. `2020-05-21T00:00:00+0000`.'
        ),
      limit: z
        .number()
        .int()
        .min(1)
        .max(1000)
        .optional()
        .default(100)
        .describe(
          'Specify a pagination limit (number of results per page) for your API request. Default limit value is `100`, maximum allowed limit value is `1000`.'
        ),
      offset: z
        .number()
        .int()
        .min(0)
        .optional()
        .default(0)
        .describe(
          'Specify a pagination offset value for your API request. Example: An offset value of `100` combined with a limit value of 10 would show results 100-110. Default value is `0`, starting with the first available result.'
        ),
    };
  • Tool definition object exporting the name, description, schema, and handler.
    export const getDividendsDataTool: MarketstackToolDefinition = {
      name: 'get_dividends_data',
      description: 'Look up information about the stock dividend for different symbols.',
      inputSchemaShape: getDividendsDataInputSchemaShape,
      handler: getDividendsDataHandler,
    };
  • MCP server registration of the get_dividends_data tool using server.tool().
    server.tool(
      getDividendsDataTool.name,
      getDividendsDataTool.description,
      getDividendsDataTool.inputSchemaShape,
      wrapToolHandler((input) => getDividendsDataTool.handler(input, client))
    );
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 'look up' which implies a read operation, but doesn't specify any behavioral traits such as rate limits, authentication requirements, data freshness, or error handling. For a tool with 6 parameters and no annotations, this is a significant gap in transparency.

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 states the core purpose without unnecessary words. It's appropriately sized for a data lookup tool and front-loads the essential information. Every word earns its place in this concise formulation.

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 complexity (6 parameters, no output schema, no annotations), the description is incomplete. It doesn't address what information is returned about dividends, how results are structured, or any limitations beyond what's implied by parameters. For a financial data tool with multiple filtering options, more context about the nature of dividend data returned would be helpful.

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 all parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema. It mentions 'symbols' in a general way but doesn't provide context beyond the schema's detailed descriptions. Baseline 3 is appropriate when the schema does the heavy lifting.

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: 'Look up information about the stock dividend for different symbols.' It specifies the verb ('look up') and resource ('stock dividend'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'get_splits_data' or 'get_ticker_details', which might also involve stock data retrieval.

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 many sibling tools for financial data (e.g., 'get_intraday_data', 'get_splits_data'), there's no indication of when dividend data is appropriate or what distinguishes it from other stock information tools. This leaves the agent to guess based on tool names alone.

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

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/matteoantoci/mcp-marketstack'

If you have feedback or need assistance with the MCP directory API, please join our Discord server