How to Use the Ghostfolio (Investment Tracker) MCP in Vercel AI SDK

Q: Can this integration handle multiple investment accounts at once?

Yes, your agent can call listaccounts to fetch all active ledgers before executing modifications. From there, it can target specific accounts using updateaccount based on the user's explicit instructions.

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Connect Ghostfolio (Investment Tracker) MCP to Vercel AI SDK

Create your Vinkius account to connect Ghostfolio (Investment Tracker) to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Ghostfolio (Investment Tracker) with Vercel AI SDK

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Live Portfolio Performance Streaming

The `get_portfolio_summary` tool gives your Vercel AI SDK application instant access to net worth, performance percentages, and absolute returns. Instead of waiting for a full page reload, your Vercel AI SDK agent streams these Ghostfolio metrics directly into your UI components. This direct connection means you can build interactive Ghostfolio dashboards where users ask about their asset allocation and watch the numbers populate on screen via Vercel AI SDK. The MCP client handles the heavy lifting, letting you feed raw valuation data straight from Ghostfolio into your client-side React state.

On-the-Fly Transaction Logging via MCP Server

Run the numbers and log new trades instantly using `create_activity` and `delete_activity` within your Vercel AI SDK streaming interface. Your Vercel AI SDK client parses natural language prompts like 'I bought 10 shares of Apple today' and turns them into structured Ghostfolio transaction records. Since this MCP Server operates on Edge-compatible runtimes, your Vercel AI SDK users get zero-latency updates when tracking their buy and sell history. No bulky server-side middleware stands between your Vercel AI SDK chat box and their actual Ghostfolio ledger.

Real-Time Asset Valuation and Pricing

The `get_market_data_price` tool fetches current asset prices to update your active Ghostfolio holdings without lag inside your Vercel AI SDK app. Your Vercel AI SDK client calls this tool to verify current market rates before calculating total Ghostfolio portfolio values. By combining this with `get_portfolio_holdings`, your Vercel AI SDK app shows exact, up-to-the-minute asset distributions. It keeps your Vercel AI SDK interface accurate without requiring manual database syncs or scheduled cron jobs in Ghostfolio.

Setup guide

Set up Ghostfolio (Investment Tracker) MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Ghostfolio (Investment Tracker) tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Ghostfolio (Investment Tracker) transactions",
});

console.log(text);
await mcpClient.close();

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Ghostfolio. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Ghostfolio (Investment Tracker) MCP in Vercel AI SDK

You pass your Ghostfolio security credentials using the authProvider option when configuring the MCP client. This keeps your API tokens secure in your environment variables while allowing the SDK to sign requests on the fly.

Yes, you can stream real-time JSON payloads directly into your frontend. By calling `get_portfolio_holdings` through the SDK's streamText function, the tool outputs render live as the model processes the financial data.

First, install the necessary packages with npm, then instantiate the MCP client using createMCPClient with your HTTP transport url. Pass the tools directly to your text generation functions and remember to close the client connection when the request finishes.

Yes, your agent can call `list_accounts` to fetch all active ledgers before executing modifications. From there, it can target specific accounts using `update_account` based on the user's explicit instructions.

This MCP Server only handles your personal transaction records, account balances, and asset holdings through an ephemeral V8 sandbox. Your credentials never touch public logs, and the connection closes immediately after executing portfolio updates.

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