How to Use the Chatham Financial MCP in Mastra AI

Build resilient financial workflows with Mastra AI by connecting directly to Chatham Financial for automated hedge accounting.

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Connect Chatham Financial MCP to Mastra AI

Create your Vinkius account to connect Chatham Financial to Mastra AI 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 Chatham Financial with Mastra AI

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Entity & Portfolio Mapping

`list_chatham_entities` and `list_chatham_portfolios` map your corporate structure and debt obligations directly into Mastra AI workflows using this MCP Server. Your agent queries the account configuration first, then branches execution based on which legal entities hold active positions. Setting this up requires passing the tools into your agent definition. The framework automatically handles rate limits from the Chatham API, applying exponential backoff if a portfolio request takes too long to resolve.

Mastra AI Workflows for Chatham Financial MCP

`get_trade_valuations` and `get_chatham_market_data` feed benchmark rates and pricing history into your conditional logic. You define a step that checks current valuations, and if the mark-to-market value drops below a specific threshold, the workflow triggers an alert. Failing valuation checks do not break your application. Mastra catches the error, retries the pricing request using an alternative forward curve, and notifies the risk team if the issue persists.

Automated Accounting Workflows

`get_trade_accounting` and `get_hedge_effectiveness` pull compliance test results into your automated reporting pipelines. Combined with `list_trade_payments`, your agent builds a complete picture of cash flows and accounting designations for any given transaction. We added support for human-in-the-loop approvals on these specific endpoints. You can configure the workflow so a financial controller signs off before the system publishes the final hedge effectiveness numbers to your general ledger.

Setup guide

Set up Chatham Financial MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Chatham Financial tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "chatham-financial-mcp-client",
  servers: {
    "chatham-financial-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Chatham Financial Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Chatham Financial tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Chatham Financial transactions"
);
console.log(result.text);

Get your connection token →

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 Mastra AI

Initialize a new client and define your Vinkius endpoint in the servers object. Call the list tools method and spread the output into your agent's tool array. Mastra detects the streamable HTTP transport automatically.

Built-in exponential backoff handles API timeouts natively. If a request for complex derivative valuations fails, the workflow engine pauses and attempts the call again without requiring custom retry logic.

Setting the approval flag to true pauses the agent execution before it fetches sensitive information. A human operator reviews the intent, approves the request, and the workflow resumes fetching the payment schedules.

The framework parses the JSON response and stores the benchmark rates in the workflow memory. Subsequent steps read this state to execute conditional branches based on the forward curve metrics.

Vinkius routes your compliance test results through an isolated, single-use execution environment. The memory space holding your accounting designations is purged the millisecond the request completes. We do not log payload contents or retain your authentication tokens.

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