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MissionSquad

MCP Avantage

by MissionSquad

technicalIndicators_dema

Calculate Double Exponential Moving Average (DEMA) for financial analysis using stock symbols, time intervals, and price types to identify trends and generate trading signals.

Instructions

Double Exponential Moving Average (DEMA)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesThe stock symbol (e.g., "IBM").
intervalYesTime interval (e.g., "daily", "60min", "weekly"). Check Alpha Vantage docs for valid intervals per indicator.
datatypeNoData format for the response.json
monthNoSpecific month for intraday intervals (YYYY-MM format).
time_periodYesNumber of data points used to calculate the indicator.
series_typeYesThe desired price type.

Implementation Reference

  • src/index.ts:1028-1042 (registration)
    Registers the 'technicalIndicators_dema' MCP tool with name, description, input schema, and inline execute handler that delegates to executeAvantageTool and the AVantage library's dema method.
    server.addTool({ name: "technicalIndicators_dema", description: "Double Exponential Moving Average (DEMA)", parameters: schemas.TechnicalIndicatorsTimeSeriesIndicatorParamsSchema, execute: ( args, context // Let type be inferred ) => executeAvantageTool( "technicalIndicators_dema", args, context, (av, params) => av.technicalIndicators.dema(params) ), });
  • The execute handler function for the tool, which calls the generic executeAvantageTool helper passing the AVantage library's technicalIndicators.dema method.
    execute: ( args, context // Let type be inferred ) => executeAvantageTool( "technicalIndicators_dema", args, context, (av, params) => av.technicalIndicators.dema(params) ),
  • Defines the Zod input parameters schema for the tool: symbol, interval, optional datatype/month, plus time_period and series_type.
    export const TechnicalIndicatorsTimeSeriesIndicatorParamsSchema = TechnicalIndicatorsCommonIndicatorParamsSchema.extend({ time_period: z.string().describe('Number of data points used to calculate the indicator.'), // Using string as AV API expects string series_type: SeriesTypeSchema, }).describe('Parameters for time series based technical indicators.')
  • Generic helper function used by all tools (including this one) to resolve API key, manage AVantage client instance via resource manager, invoke the specified library method, handle errors, and return JSON string of 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}` ); } }
  • Base schema extended by the tool's parameters schema, defining common fields: symbol, interval, datatype, month.
    export const TechnicalIndicatorsCommonIndicatorParamsSchema = z.object({ symbol: z.string().describe('The stock symbol (e.g., "IBM").'), interval: z.string().describe('Time interval (e.g., "daily", "60min", "weekly"). Check Alpha Vantage docs for valid intervals per indicator.'), datatype: DatatypeSchema.default('json').optional(), month: z.string().optional().describe('Specific month for intraday intervals (YYYY-MM format).'), }).describe('Common parameters for many technical indicators.')
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