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MissionSquad

MCP Avantage

by MissionSquad

fundamentalData_ipoCalendar

Access upcoming IPO calendar data to track new stock market listings and identify investment opportunities using Alpha Vantage financial information.

Instructions

Fetches upcoming IPO calendar (CSV endpoint).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/index.ts:935-946 (registration)
    MCP tool registration for 'fundamentalData_ipoCalendar'. Specifies name, description, empty Zod input schema, and execute handler that wraps Avantage library's fundamentalData.ipoCalendar() call.
    server.addTool({
      name: "fundamentalData_ipoCalendar",
      description: "Fetches upcoming IPO calendar (CSV endpoint).",
      parameters: z.object({}), // No parameters
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool("fundamentalData_ipoCalendar", args, context, (av) =>
          av.fundamentalData.ipoCalendar()
        ),
    });
  • Input schema definition: empty object (no parameters required for this tool). Uses Zod directly.
    parameters: z.object({}), // No parameters
  • Tool execute handler: calls generic executeAvantageTool with the specific Avantage method av.fundamentalData.ipoCalendar() (no args needed). This is the core logic dispatching to the underlying library.
    execute: (
      args,
      context // Let type be inferred
    ) =>
      executeAvantageTool("fundamentalData_ipoCalendar", args, context, (av) =>
        av.fundamentalData.ipoCalendar()
      ),
  • Generic helper function used by all tools (including this one) for executing Avantage library methods. Manages API key resolution, AVantage instance caching via resourceManager, performs the library call, handles responses/errors, and 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}`
        );
      }
    }
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions 'CSV endpoint' which hints at data format, but doesn't disclose rate limits, authentication needs, data freshness, scope (global/regional), or what 'upcoming' timeframe means. For a data-fetching tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

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?

Extremely concise single sentence with zero waste. Every word earns its place: 'Fetches' (action), 'upcoming IPO calendar' (resource), 'CSV endpoint' (implementation detail). Front-loaded with the core purpose.

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 zero-parameter tool with no output schema, the description is minimally adequate but could be more complete. It identifies the resource and format, but lacks context about data scope, freshness, limitations, or how it differs from similar tools. Without annotations or output schema, the agent has limited understanding of what to expect from this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0 parameters and 100% schema description coverage, the baseline is high. The description doesn't need to explain parameters, though it could mention that this tool requires no inputs (which is implied by the empty schema). The mention of 'CSV endpoint' adds some context about output format beyond what the schema provides.

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 ('Fetches') and resource ('upcoming IPO calendar'), making the purpose immediately understandable. It distinguishes from siblings like fundamentalData_earningsCalendar by specifying IPO focus, though it doesn't explicitly contrast with all sibling tools.

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 on when to use this tool versus alternatives like fundamentalData_earningsCalendar or other calendar-related tools. The description mentions it's a CSV endpoint, but doesn't explain when this format is preferable or what limitations it might have compared to other data formats.

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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