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MCP Avantage

by MissionSquad

economicIndicators_treasuryYield

Access US Treasury yield curve data for various maturities to analyze bond market trends and economic conditions. Retrieve data in JSON or CSV format with customizable intervals and maturity periods.

Instructions

Retrieves US Treasury yield curve data for various maturities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intervalNoTime interval.monthly
maturityNoTreasury maturity period.10year
datatypeNoData format for the response.json

Implementation Reference

  • src/index.ts:583-597 (registration)
    Registers the 'economicIndicators_treasuryYield' MCP tool with the FastMCP server. Specifies the tool name, description, input schema, and an inline execute handler that uses the generic executeAvantageTool to call the AVantage library's economicIndicators.treasuryYield method.
    server.addTool({
      name: "economicIndicators_treasuryYield",
      description: "Retrieves US Treasury yield curve data for various maturities.",
      parameters: schemas.EconomicIndicatorsTreasuryYieldParamsSchema,
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool(
          "economicIndicators_treasuryYield",
          args,
          context,
          (av, params) => av.economicIndicators.treasuryYield(params)
        ),
    });
  • Defines the Zod validation schema for the tool's input parameters: interval (daily, weekly, or monthly; default monthly), maturity (specific treasury bond maturities like 10year; default 10year), and datatype (json or csv; default json).
    export const EconomicIndicatorsTreasuryYieldParamsSchema = z.object({
      interval: DailyWeeklyMonthlySchema.default('monthly').optional(),
      maturity: z.enum(['3month', '2year', '5year', '7year', '10year', '30year']).default('10year').optional().describe('Treasury maturity period.'),
      datatype: DatatypeSchema.default('json').optional(),
    }).describe('Parameters for fetching Treasury Yield data.')
  • Generic handler function shared across all tools. Resolves API key, manages AVantage client instances using resourceManager, invokes the library method provided in the lambda (av.economicIndicators.treasuryYield for this tool), handles errors with UserError, and returns JSON.stringify(result.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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that data is retrieved, implying a read-only operation, but fails to mention any behavioral traits like rate limits, authentication requirements, data freshness, or error handling. This is a significant gap for a tool with no annotation coverage.

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 fluff or redundancy. It is appropriately sized and front-loaded, making it easy 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 complexity of financial data retrieval, no annotations, and no output schema, the description is incomplete. It lacks details on return format, data structure, potential errors, or usage constraints, leaving significant gaps for an agent to understand how to effectively use this tool.

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 enums and defaults for all parameters (interval, maturity, datatype). The description adds no additional semantic context beyond implying 'various maturities,' which is already covered by the schema's enum. Baseline score of 3 is appropriate as 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 action ('Retrieves') and resource ('US Treasury yield curve data for various maturities'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'economicIndicators_federalFundsRate' or 'economicIndicators_realGDP', which might also retrieve economic data, though the specific focus on Treasury yields is reasonably distinct.

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, such as other economic indicators or financial data tools in the sibling list. It lacks any mention of context, prerequisites, or exclusions, leaving the agent to infer usage based solely on the tool name and description.

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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