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MCP Avantage

by MissionSquad

economicIndicators_realGDP

Retrieve US Real Gross Domestic Product (GDP) data in annual or quarterly intervals to analyze economic performance and trends.

Instructions

Retrieves US Real Gross Domestic Product (GDP) data.

Input Schema

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

Implementation Reference

  • src/index.ts:551-565 (registration)
    Registers the 'economicIndicators_realGDP' tool with the MCP server using FastMCP. Includes name, description, input schema reference, and an inline execute handler that uses the generic executeAvantageTool to call the AVantage library's economicIndicators.realGDP method.
    server.addTool({
      name: "economicIndicators_realGDP",
      description: "Retrieves US Real Gross Domestic Product (GDP) data.",
      parameters: schemas.EconomicIndicatorsRealGDPParamsSchema,
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool(
          "economicIndicators_realGDP",
          args,
          context,
          (av, params) => av.economicIndicators.realGDP(params)
        ),
    });
  • Zod schema defining the input parameters for the economicIndicators_realGDP tool: optional interval (annual/quarterly) and datatype.
    export const EconomicIndicatorsRealGDPParamsSchema = z.object({
      interval: z.enum(['annual', 'quarterly']).default('annual').optional().describe('Time interval.'),
      datatype: DatatypeSchema.default('json').optional(),
    }).describe('Parameters for fetching Real GDP data.')
  • Generic handler function shared across all tools, implementing the core execution logic: resolves API key, manages AVantage client instance via resource manager, invokes the library method specific to the tool, handles responses and errors, returns JSON string.
    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}`
        );
      }
    }
  • Uses resourceManager to cache and manage AVantage API client instances keyed by API key, ensuring efficient reuse and cleanup.
      const newInfo: ResourceInfo<T> = {
        resource: newResource,
        lastUsed: Date.now(),
        instanceId: instanceId,
        resourceType: resourceType,
        cacheKey: key,
        cleanupFn: cleanupFn,
      }
      this.resources.set(key, newInfo)
      logger.info(
        `Successfully created resource (Type: ${resourceType}, Instance ID: ${instanceId})`,
      )
      return newResource
    } catch (error) {
      logger.error(
        `Failed to create resource (Type: ${resourceType}) for key ${key}: ${error instanceof Error ? error.message : String(error)}`,
        error,
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Retrieves', implying a read-only operation, but doesn't mention any behavioral traits like rate limits, data freshness, authentication needs, or error handling. This leaves significant gaps in understanding how the tool behaves in practice.

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 purpose without any wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.

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 simple data retrieval tool with two well-documented parameters and no output schema, the description is minimally adequate. However, it lacks context about the data source, time ranges, or what the returned data looks like, which could help the agent use it more effectively. With no annotations, more behavioral detail would improve completeness.

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 input schema has 100% description coverage with clear enum values and defaults for both parameters. The description doesn't add any parameter semantics beyond what's in the schema, but since the schema is comprehensive, the baseline score of 3 is appropriate—adequate but no extra value from the description.

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 action ('Retrieves') and resource ('US Real Gross Domestic Product (GDP) data'), making the purpose immediately understandable. However, it doesn't differentiate from its sibling 'economicIndicators_realGDPPerCapita', which retrieves similar but distinct data, leaving some ambiguity about when to choose one over the other.

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 guidance is provided on when to use this tool versus alternatives, such as other economic indicators or the sibling realGDPPerCapita tool. The description lacks context about typical use cases or prerequisites, leaving the agent to infer usage based solely on the tool name and parameters.

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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