Skip to main content
Glama
MissionSquad

MCP Avantage

by MissionSquad

forex_monthly

Retrieve monthly historical exchange rate data for currency pairs to analyze long-term forex trends and performance.

Instructions

Fetches monthly time series data for a Forex pair.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_symbolYesThe currency symbol to convert from (e.g., "EUR").
to_symbolYesThe currency symbol to convert to (e.g., "USD").
datatypeNoData format for the response.json

Implementation Reference

  • The handler function for the 'forex_monthly' tool, registered via server.addTool. It invokes executeAvantageTool which calls the Alpha Vantage forex.monthly API method with validated parameters.
    server.addTool({
      name: "forex_monthly",
      description: "Fetches monthly time series data for a Forex pair.",
      parameters: schemas.ForexWeeklyMonthlyParamsSchema,
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool("forex_monthly", args, context, (av, params) =>
          av.forex.monthly(params)
        ),
    });
  • Zod schema defining input parameters for the forex_monthly tool (shared with forex_weekly): from_symbol, to_symbol, and optional datatype.
    export const ForexWeeklyMonthlyParamsSchema = z.object({
      from_symbol: z.string().describe('The currency symbol to convert from (e.g., "EUR").'),
      to_symbol: z.string().describe('The currency symbol to convert to (e.g., "USD").'),
      datatype: DatatypeSchema.default('json').optional(),
    }).describe('Parameters for fetching weekly/monthly Forex time series data.')
  • src/index.ts:762-773 (registration)
    MCP server registration of the 'forex_monthly' tool, specifying name, description, input schema, and handler.
    server.addTool({
      name: "forex_monthly",
      description: "Fetches monthly time series data for a Forex pair.",
      parameters: schemas.ForexWeeklyMonthlyParamsSchema,
      execute: (
        args,
        context // Let type be inferred
      ) =>
        executeAvantageTool("forex_monthly", args, context, (av, params) =>
          av.forex.monthly(params)
        ),
    });
  • Shared utility function that orchestrates the execution for all Alpha Vantage tools, including client creation/caching, API calls, and error handling. Specifically used by forex_monthly to call av.forex.monthly(params).
    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. While 'fetches' implies a read-only operation, the description doesn't address important behavioral aspects like rate limits, authentication requirements, data freshness, error conditions, or what the response structure looks like. For a data-fetching tool with zero annotation coverage, this is insufficient.

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 no wasted words. It's appropriately sized for a straightforward data-fetching tool and front-loads the essential information.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the monthly time series data looks like, what time periods are available, whether there are data limitations, or how to interpret results. For a data retrieval tool with no structured output documentation, the description should provide more context about the returned data.

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 adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 ('monthly time series data for a Forex pair'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'forex_daily', 'forex_weekly', or 'forex_intraday', which would require mentioning the specific time granularity differentiation.

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 multiple sibling tools for different Forex timeframes (daily, weekly, intraday) and other related tools, there's no indication of when monthly data is appropriate or what distinguishes this from other frequency options.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/MissionSquad/mcp-avantage'

If you have feedback or need assistance with the MCP directory API, please join our Discord server