How to Use the Chatham Financial MCP in OpenAI Agents SDK

Q: Can the SDK automatically find my tools?

Yes. The framework auto-discovers endpoints like listchathamtransactions as soon as you connect the server. You skip the manual definitions entirely.

Build production-grade financial agents with OpenAI Agents SDK. Validate trade data and execute safe hedge workflows.

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Connect Chatham Financial MCP to OpenAI Agents SDK

Create your Vinkius account to connect Chatham Financial to OpenAI Agents 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 Chatham Financial with OpenAI Agents SDK

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Pull benchmark rates into your MCP Server

The `get_chatham_market_data` tool streams forward curves and current benchmark rates directly into your agent context. Your production system relies on accurate numbers, and this endpoint delivers exactly what Chatham Financial calculates for the market. Combine this with `get_trade_valuations` to run historical pricing comparisons. The OpenAI Agents SDK guardrails ensure your agent validates the valuation dates before passing any numbers to downstream reporting functions.

Run strict hedge effectiveness checks

The `get_hedge_effectiveness` tool pulls test results for specific transactions, feeding risk data directly into your compliance logs. Tracking financial risk requires absolute precision. If a test fails, you can trigger a handoff to an accounting agent that calls `get_trade_accounting` to pull the exact designation details. Full tracing in the OpenAI dashboard means you always know why an agent flagged a specific trade.

Map entities to payment schedules

The `list_chatham_entities` tool grabs your configured accounts so your agent knows exactly who owns what. Managing complex corporate structures means mapping legal entities to actual cash flows. From there, your agent chains `list_chatham_portfolios` and `list_trade_payments` to build out upcoming payment histories. You get a complete picture of transaction liabilities without writing custom MCP wrappers.

Setup guide

Set up Chatham Financial MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Chatham Financial tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Chatham Financial tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Chatham Financial tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Chatham Financial Agent",
            instructions="You have access to Chatham Financial tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 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 OpenAI Agents SDK

Install openai-agents via pip. Initialize MCPServerStreamableHttp with your Vinkius endpoint URL and pass it to your Agent constructor's mcp_servers list. Set cacheToolsList=True to speed up discovery.

Yes. The framework auto-discovers endpoints like list_chatham_transactions as soon as you connect the server. You skip the manual definitions entirely.

Financial data needs strict guardrails. This SDK lets you enforce safety constraints on tools like get_trade_valuations, preventing your agent from hallucinating historical trade prices.

No. The MCP standard handles the schema definitions automatically. Your agent reads the inputs and outputs natively.

Your transaction histories and payment schedules route through a V8 Isolate Sandbox. Vinkius drops the container the second your agent finishes its request. Nothing persists in our infrastructure.

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