Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@AlphaVantage MCP Server Show me the latest income statement for Apple"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
This project implements an Azure Function that serves as a bridge between an Agent as a MCP Server and the AlphaVantage Financial API. It allows AI agents to access financial data and perform financial analysis through tools exposed via MCP.
The Azure Function exposes the following financial data endpoints as MCP tools:
Company Overview
Income Statement
Balance Sheet
Cash Flow
Earnings Report
There is a demo agent created with PydanticAI in the agent directory that can be used to test the MCP server. More information Demo Agent file.
An Azure subscription
Python 3.11
An AlphaVantage API key (see AlphaVantage)
Related MCP server: MCP Financial Data Gateway
Clone this repository
Create a virtual environment and install dependencies:
uv sync --frozenCreate a local.settings.json file in the src directory with your AlphaVantage API key:
{
"IsEncrypted": false,
"Values": {
"FUNCTIONS_WORKER_RUNTIME": "python",
"AzureWebJobsStorage": "UseDevelopmentStorage=true",
"ALPHAVANTAGE_API_KEY": "your-alphavantage-api-key"
}
}Run the function locally:
cd src
func startLog in to Azure:
azd auth loginDeploy the application:
azd upThis will provision the necessary Azure resources and deploy the Function App.
Note: For setting up environment variables, refer to the Adding Environment Variables section.
After deployment, retrieve your MCP extension system key:
az functionapp keys list \
--resource-group <resource_group> \
--name <function_app_name>Your MCP endpoint URL will be:
https://<funcappname>.azurewebsites.net/runtime/webhooks/mcp/sse?code=<your-mcp-extension-system-key>You can add environment variables to your Azure Function in two ways:
Add your environment variables to the infra/main.parameters.json file:
{
"parameters": {
// Other parameters...
"functionAppEnvironmentVariables": {
"value": {
"ALPHAVANTAGE_API_KEY": "your-api-key",
"MY_VARIABLE": "my-value"
}
}
}
}Then deploy with:
azd upaz functionapp config appsettings set \
--name <function_app_name> \
--resource-group <resource-group> \
--settings ALPHAVANTAGE_API_KEY=<your-api-key>This project includes a .vscode/mcp.json configuration file that helps you connect to your MCP endpoint during development. This file contains:
Input definitions - Prompts for:
The Azure Functions MCP Extension System Key (stored securely)
Your Azure Functions App Name
Server configurations:
remote-mcp-function - Connects to your deployed Azure Function using the inputs above
local-mcp-function - Connects to a locally running function on port 7071
This allows you to test your MCP tools directly from VS Code during development, either against your local function app or your deployed Azure instance.
The agent directory contains an example of how to use this MCP endpoint with an AI agent using the Agno framework. You can use this as a starting point for your own financial analysis agent.
The infrastructure code for this project was adapted from Azure-Samples/remote-mcp-functions-python, which provides a template for deploying Python functions as remote MCP tools on Azure.
This server cannot be deployed
Your agent needs company financials it can compute on — statements, ratios, earnings, estimates, filings and insider activity as structured data, not a PDF. **What you can ask for** • "Give me 8 quarters of income statement, balance sheet and cash flow for this ticker." • "What do analysts estimate for next quarter, and how did the last four surprise?" • "Find this exact line item across every filing." • "Who bought or sold as an insider in the last 90 days?" • "Screen for profitable companies under this valuation with growing revenue." **How to use it** Point any MCP client at https://mcp.aisa.one/marketpulse/mcp and sign in with OAuth — there is no key to create or paste. 21 tools: prices and snapshots, income statements, balance sheets, cash-flow statements, financial metrics and snapshots, earnings, analyst estimates, company facts, filings and filing items, line-item search, a screener, insider trades, macro interest rates, news, plus EDINET documents and filing digests for Japanese issuers. **Why this rather than the source** Statements as fields you can compute on, and a screener in the same place. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Read the fundamentals here, then ask the same agent what social is saying about the ticker — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/finance/mcp for equities, crypto and prediction markets in one place.
Real SEC, 13F, insider, congress & macro data your AI agent can cite. Hosted MCP, 24 tools.
Your agent needs markets — prices and fundamentals for listed companies, the filings behind them, crypto, and what the prediction markets put the odds at. **What you can ask for** • "Pull this company's income statement, cash flow and balance sheet for the last 8 quarters." • "What did insiders buy or sell, and when?" • "Snapshot prices for these 50 tickers, then the OHLC history for the three that moved." • "What are the current odds on this event across Kalshi and Polymarket?" • "Screen for companies matching these financial criteria." **How to use it** Point any MCP client at https://mcp.aisa.one/finance/mcp and sign in with OAuth — there is no key to create or paste. 49 tools: prices and snapshots, income statements, balance sheets and cash flows, metrics and ratios, earnings and analyst estimates, filings and line-item search, insider trades, macro interest rates, news, a screener; CoinGecko spot prices, market tables, OHLC, per-venue tickers and trending; Kalshi and Polymarket markets and trades; plus EDINET filings for Japan. **Why this rather than the source** Equities, crypto and event markets behind one account, so a cross-asset question is one conversation. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Read the number here, then ask the same agent what X is saying about the ticker today — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/marketpulse/mcp · /crypto-market-data/mcp · /prediction-market-data/mcp · /stock-pulse/mcp for one slice each.
Alpha Vantage MCP — Stock market data, fundamentals, and earnings
