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MCP Avantage

by MissionSquad

crypto_weekly

Get weekly cryptocurrency price data for analysis and tracking. Specify symbol, market, and format to retrieve time series information.

Instructions

Fetches weekly 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:524-535 (registration)
    MCP server registration of the 'crypto_weekly' tool, including its execute handler function that invokes the Alpha Vantage crypto.weekly API endpoint via the shared executeAvantageTool helper.
    server.addTool({
      name: "crypto_weekly",
      description: "Fetches weekly time series data for a cryptocurrency.",
      parameters: schemas.CryptoTimeSeriesParamsSchema,
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool("crypto_weekly", args, context, (av, params) =>
          av.crypto.weekly(params)
        ),
    });
  • Zod schema defining input parameters for crypto time series tools (daily, weekly, monthly), used by crypto_weekly.
    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.')
  • Shared utility function that manages Alpha Vantage client instances, performs API calls, and handles responses/errors for all tools including crypto_weekly.
    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 full burden for behavioral disclosure. It states 'fetches' which implies a read operation, but doesn't cover important aspects like rate limits, authentication requirements, data freshness, error handling, or response format details. For a data-fetching tool with no annotation support, 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 gets straight to the point with zero wasted words. It's appropriately sized for a straightforward data-fetching tool and front-loads the core functionality without unnecessary elaboration.

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?

For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the weekly time series data contains (e.g., OHLC values, volume), how results are structured, or any behavioral constraints. Given the complexity of financial data and the lack of structured metadata, the description should provide more context about the operation and its results.

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?

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain what 'weekly time series' includes or provide examples beyond the basic fetch action). This meets the baseline expectation when schema coverage is complete.

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 ('weekly time series data for a cryptocurrency'), making the purpose immediately understandable. However, it doesn't explicitly distinguish this tool from its sibling crypto tools (like crypto_daily, crypto_weeklyAdjusted, or crypto_monthly), which would require mentioning what makes 'weekly' data unique or when to prefer it over other timeframes.

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., crypto_daily, crypto_weeklyAdjusted, forex_weekly), there's no indication of when weekly crypto data is appropriate compared to daily, adjusted, or other asset classes. This leaves the agent without context for tool selection.

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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