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MCP Avantage

by MissionSquad

economicIndicators_federalFundsRate

Retrieve the effective federal funds rate data in JSON or CSV format for daily, weekly, or monthly intervals to analyze monetary policy and economic conditions.

Instructions

Retrieves the effective federal funds rate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intervalNoTime interval.monthly
datatypeNoData format for the response.json

Implementation Reference

  • MCP server tool registration including the inline execute handler function for 'economicIndicators_federalFundsRate'. The handler delegates execution to the generic executeAvantageTool helper, which calls the Alpha Vantage SDK method av.economicIndicators.federalFundsRate(params).
    server.addTool({
      name: "economicIndicators_federalFundsRate",
      description: "Retrieves the effective federal funds rate.",
      parameters: schemas.EconomicIndicatorsFederalFundsRateParamsSchema,
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool(
          "economicIndicators_federalFundsRate",
          args,
          context,
          (av, params) => av.economicIndicators.federalFundsRate(params)
        ),
    });
  • Zod schema defining the input parameters (interval and datatype) for the economicIndicators_federalFundsRate tool.
    export const EconomicIndicatorsFederalFundsRateParamsSchema = z.object({
      interval: DailyWeeklyMonthlySchema.default('monthly').optional(),
      datatype: DatatypeSchema.default('json').optional(),
    }).describe('Parameters for fetching Federal Funds Rate data.')
  • Generic helper function shared across all MCP tools. Manages Alpha Vantage client lifecycle via resourceManager, resolves API key, invokes the tool-specific SDK method, handles errors, and returns JSON stringified data.
    async function executeAvantageTool<TArgs, TResult>(
      toolName: string,
      args: TArgs,
      context: Context<Record<string, unknown> | undefined>, // Use the imported Context type directly
      avantageMethod: (
        av: AVantage,
        args: TArgs
      ) => Promise<{ error?: boolean; reason?: string; data?: TResult }>
    ): Promise<string> {
      logger.info(`Executing '${toolName}' tool for request ID: ${context}`);
      logger.debug(`Args for ${toolName}: ${JSON.stringify(args)}`);
    
      // --- Authentication & Resource Management ---
      // Access extraArgs safely - it might be null or undefined
      const extraArgsApiKey = context.extraArgs?.apiKey as string | undefined;
      const apiKey = extraArgsApiKey || config.apiKey;
    
      if (!apiKey) {
        logger.error(`'${toolName}' failed: Alpha Vantage API key missing.`);
        throw new UserError(apiKeyErrorMessage);
      }
      logger.debug(
        `Using AV API key (source: ${extraArgsApiKey ? "extraArgs" : "environment"}) for ${toolName}`
      );
    
      try {
        // Get or create AVantage instance managed by ResourceManager
        const av = await resourceManager.getResource<AVantage>(
          apiKey, // Cache key is the resolved API key
          "avantage_client", // Type identifier for logging
          async (key) => {
            // Factory Function
            logger.info(
              `Creating new AVantage instance for key ending ...${key.slice(-4)}`
            );
            // AVantage library reads AV_PREMIUM from process.env internally
            return new AVantage(key);
          },
          async (avInstance) => {
            // Cleanup Function (no-op needed for AVantage)
            logger.debug(`Destroying AVantage instance (no-op)`);
          }
        );
    
        // --- Library Call ---
        const result = await avantageMethod(av, args);
    
        // --- Response Handling ---
        if (result.error) {
          logger.warn(
            `'${toolName}' failed. Reason from avantage: ${result.reason}`
          );
          throw new UserError(result.reason || `Tool '${toolName}' failed.`);
        }
    
        if (result.data === undefined || result.data === null) {
          logger.warn(`'${toolName}' completed successfully but returned no data.`);
          return "null"; // Return string "null" for empty data
        }
    
        logger.info(`'${toolName}' completed successfully.`);
        // Stringify the data part of the response
        return JSON.stringify(result.data);
      } catch (error: any) {
        logger.error(
          `Error during execution of '${toolName}': ${error.message}`,
          error
        );
        // If it's already a UserError, rethrow it
        if (error instanceof UserError) {
          throw error;
        }
        // Otherwise, wrap it in a UserError
        throw new UserError(
          `An unexpected error occurred while executing tool '${toolName}': ${error.message}`
        );
      }
    }
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 states the tool 'Retrieves' data, implying a read-only operation, but doesn't mention any behavioral traits such as rate limits, authentication requirements, data freshness, or potential errors. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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, clear sentence with zero wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action without unnecessary elaboration, making it highly concise and well-structured.

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?

Given the tool's low complexity (2 optional parameters, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks context on usage, behavioral details, or output format. While adequate for a simple retrieval tool, it doesn't fully compensate for the absence of annotations or output schema, leaving room for improvement in guiding 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?

The schema description coverage is 100%, with both parameters ('interval' and 'datatype') well-documented in the input schema, including enums and defaults. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 for adequate coverage without extra value.

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 with a specific verb ('Retrieves') and resource ('the effective federal funds rate'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'economicIndicators_treasuryYield' or 'economicIndicators_inflation', which are related economic indicators but serve different purposes.

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 available (e.g., other economic indicators like CPI or unemployment rate), there's no indication of when this specific rate is appropriate, what context it applies to, or any prerequisites for usage.

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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