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How to Use the Chatham Financial MCP in Vercel AI SDK

Stream Chatham Financial trade valuations and hedge accounting data directly into your React frontend using the Vercel AI SDK.

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…and any MCP-compatible client

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Vercel AI SDK

Connect Chatham Financial MCP to Vercel AI SDK

Create your Vinkius account to connect Chatham Financial 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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Live Market Data & Pricing

`get_chatham_market_data` and `get_trade_valuations` pull live benchmark rates and historical trade pricing into your application using this MCP Server. You call these endpoints from your Next.js backend while the Vercel AI SDK streams the resulting numbers straight to the client. Users see forward curves render instantly instead of waiting for a bulk payload. Your frontend components update tick-by-tick as the server delivers the exact financial metrics requested.

Portfolio & Transaction Tracking

`list_chatham_portfolios` and `list_chatham_transactions` expose managed debt and financial trades to your user interface. Passing these tools to the generation function lets your AI client query specific portfolios and return the underlying trade details on demand. We built this so you do not have to write custom polling logic for trade execution statuses. The agent handles the parameter mapping, and your Svelte or Vue components receive the formatted transaction arrays as they arrive.

Vercel AI SDK MCP Server Integration

`get_hedge_effectiveness` and `get_trade_accounting` supply the compliance data required for financial reporting. You feed these into the streaming function to build interactive dashboards where users ask about their hedge statuses and get immediate, cited answers. Adding `list_trade_payments` to the tool array completes the picture by fetching payment schedules. Your application can now display upcoming cash flows alongside the accounting tests that validate them.

Setup guide

Set up Chatham Financial 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. 1

    Install dependencies

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

  2. 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. 3

    Discover and use tools

    Call mcpClient.tools() to auto-discover all Chatham Financial tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.

  4. 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 Chatham Financial transactions",
});

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

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Chatham Financial. 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 Chatham Financial MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and instantiate the client using the create method. Pass your Vinkius endpoint URL with the HTTP transport option. Call the tools function and feed the result into your text generation stream.
Yes, the SDK handles the streaming automatically. When your agent calls the market data tools, the resulting rate arrays push to your Next.js frontend in chunks. Users watch the curve build on their screen.
The SDK catches the tool execution error and surfaces it in the response object. You can render a fallback UI component or prompt the user to refine their valuation request. Always remember to close the connection to clean up.
The underlying HTTP transport works perfectly in edge functions. You simply pass the Vinkius URL, and the server executes the financial queries remotely. No heavy binaries run on your edge nodes.
We run every request inside an ephemeral V8 Isolate sandbox that destroys itself after executing. Your legal entity identifiers and historical trade pricing never touch a persistent disk. Vinkius operates on a strict zero-trust model, routing the payload directly to the API and nowhere else.

Start using the Chatham Financial MCP today

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