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ranveer0323

Alpha Vantage Stock Analysis MCP Server

get-daily-stock-data

Retrieve daily stock market data for analysis, providing historical price information for specified stock symbols with adjustable data range options.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock symbol (e.g., IBM, AAPL)
outputsizeNoAmount of data to return (compact: latest 100 data points, full: up to 20 years of data)

Implementation Reference

  • MCP tool handler for get-daily-stock-data that invokes getStockData with daily interval and handles response/error formatting.
    async ({ symbol, outputsize = "compact" }) => {
        try {
            const data = await getStockData(symbol, "daily", outputsize);
            return {
                content: [{ type: "text", text: data }]
            };
        } catch (error) {
            return {
                content: [{ type: "text", text: `Error fetching daily stock data: ${error instanceof Error ? error.message : String(error)}` }],
                isError: true
            };
        }
    }
  • Input schema using Zod validators for the tool parameters: symbol and optional outputsize.
    {
        symbol: z.string().describe("Stock symbol (e.g., IBM, AAPL)"),
        outputsize: z.enum(["compact", "full"]).optional().describe("Amount of data to return (compact: latest 100 data points, full: up to 20 years of data)")
    },
  • src/index.ts:84-103 (registration)
    Registration of the get-daily-stock-data tool with schema and handler on the MCP server.
    server.tool(
        "get-daily-stock-data",
        {
            symbol: z.string().describe("Stock symbol (e.g., IBM, AAPL)"),
            outputsize: z.enum(["compact", "full"]).optional().describe("Amount of data to return (compact: latest 100 data points, full: up to 20 years of data)")
        },
        async ({ symbol, outputsize = "compact" }) => {
            try {
                const data = await getStockData(symbol, "daily", outputsize);
                return {
                    content: [{ type: "text", text: data }]
                };
            } catch (error) {
                return {
                    content: [{ type: "text", text: `Error fetching daily stock data: ${error instanceof Error ? error.message : String(error)}` }],
                    isError: true
                };
            }
        }
    );
  • Helper function implementing the core API call to Alpha Vantage for stock data, specifically using TIME_SERIES_DAILY for the 'daily' interval used by the tool, and formatting the response.
    export async function getStockData(symbol: string | string[], interval: string | string[] | 'daily', outputsize: string = 'compact'): Promise<string> {
        try {
            // Ensure parameters are strings, not arrays
            const symbolStr = Array.isArray(symbol) ? symbol[0] : symbol;
            const intervalStr = Array.isArray(interval) ? interval[0] : interval;
            const outputsizeStr = Array.isArray(outputsize) ? outputsize[0] : outputsize;
    
            let url: string;
            let timeSeriesKey: string;
    
            if (intervalStr === 'daily') {
                // Use TIME_SERIES_DAILY endpoint
                url = `${BASE_URL}?function=TIME_SERIES_DAILY&symbol=${symbolStr}&outputsize=${outputsizeStr}&apikey=${API_KEY}`;
                timeSeriesKey = 'Time Series (Daily)';
            } else {
                // Use TIME_SERIES_INTRADAY endpoint
                url = `${BASE_URL}?function=TIME_SERIES_INTRADAY&symbol=${symbolStr}&interval=${intervalStr}&outputsize=${outputsizeStr}&apikey=${API_KEY}`;
                timeSeriesKey = `Time Series (${intervalStr})`;
            }
    
            const response = await axios.get(url);
    
            // Check for error messages from Alpha Vantage
            if (response.data['Error Message']) {
                throw new Error(response.data['Error Message']);
            }
    
            if (response.data['Note']) {
                console.warn('API Usage Note:', response.data['Note']);
            }
    
            // Extract the time series data
            const timeSeries = response.data[timeSeriesKey];
    
            if (!timeSeries) {
                throw new Error('No time series data found in the response');
            }
    
            // Format the data
            const formattedData = formatTimeSeriesData(timeSeries, symbolStr, intervalStr);
            return formattedData;
        } catch (error) {
            if (axios.isAxiosError(error)) {
                throw new Error(`API request failed: ${error.message}`);
            }
            throw error;
        }
    }
Behavior1/5

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Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

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Completeness1/5

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

Tool has no description.

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

Parameters1/5

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

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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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