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MCP Avantage

by MissionSquad

crypto_daily

Fetch daily cryptocurrency time series data for analysis and tracking by specifying symbol and market parameters.

Instructions

Fetches daily time series data for a cryptocurrency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesThe cryptocurrency symbol (e.g., "BTC").
marketYesThe exchange market (e.g., "USD", "EUR").
datatypeNoData format for the response.json

Implementation Reference

  • src/index.ts:511-522 (registration)
    Registration of the 'crypto_daily' MCP tool, including name, description, input schema reference, and execute handler that wraps the AVantage library call.
    server.addTool({
      name: "crypto_daily",
      description: "Fetches daily time series data for a cryptocurrency.",
      parameters: schemas.CryptoTimeSeriesParamsSchema,
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool("crypto_daily", args, context, (av, params) =>
          av.crypto.daily(params)
        ),
    });
  • Zod schema defining the input parameters for the crypto_daily tool: cryptocurrency symbol, market (e.g., USD), and optional datatype.
    export const CryptoTimeSeriesParamsSchema = z.object({
      symbol: z.string().describe('The cryptocurrency symbol (e.g., "BTC").'),
      market: z.string().describe('The exchange market (e.g., "USD", "EUR").'),
      datatype: DatatypeSchema.default('json').optional(),
    }).describe('Parameters for fetching daily/weekly/monthly crypto time series data.')
  • Generic async handler function executed by crypto_daily (and other tools). Manages authentication, AVantage client lifecycle, invokes av.crypto.daily(params), processes response, and handles errors.
    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}': ${error.message}`
        );
      }
    }
  • Helper code within executeAvantageTool for obtaining/managing AVantage API client instance via resourceManager, used by crypto_daily.
    // Get or create AVantage instance managed by ResourceManager
    const av = await resourceManager.getResource<AVantage>(
      apiKey, // Cache key is the resolved API key
      "avantage_client", // Type identifier for logging
      async (key) => {
        // Factory Function
        logger.info(
          `Creating new AVantage instance for key ending ...${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)`);
      }
    );
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 'fetches' data, implying a read-only operation, but doesn't mention any behavioral traits such as rate limits, authentication requirements, data freshness, or error handling. For a data-fetching tool with zero annotation coverage, 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 directly states the tool's purpose without any wasted words. It's 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.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (fetching time series data) and the absence of both annotations and an output schema, the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and return values. With no output schema, the description should ideally hint at the response format, but it doesn't, leaving gaps in 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 documentation for all three parameters (symbol, market, datatype). The description adds no additional meaning beyond what the schema provides, as it doesn't explain parameter interactions, examples, or constraints. 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 with a specific verb ('fetches') and resource ('daily time series data for a cryptocurrency'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish itself from sibling tools like 'crypto_intraday', 'crypto_weekly', or 'crypto_monthly', which likely provide similar data at different time intervals.

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. It doesn't mention sibling tools (e.g., crypto_intraday for intraday data, crypto_weekly for weekly data) or any specific contexts where this tool is preferred. Usage is implied by the name 'daily', but no explicit guidelines are given.

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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