Can I see the mark-to-market valuation for a specific trade?

Yes! Use the `get_trade_valuations` tool with the trade ID. The agent will return the latest calculated valuation from ChathamDirect.

How do I check current SOFR or EURIBOR rates?

Use the `get_chatham_market_data` tool and specify the index (e.g., 'SOFR'). Your agent will fetch the latest benchmark rates and available forward curves.

Where do I find my Chatham API credentials?

API access is typically provided to ChathamDirect clients. Contact your Chatham Relationship Manager to request API access and obtain your API Key and Client ID.

Chatham Financial MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Chatham Financial
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Chatham Financial through Vinkius, pass the Edge URL in the `mcps` parameter and every Chatham Financial tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Chatham Financial Specialist",
    goal="Help users interact with Chatham Financial effectively",
    backstory=(
        "You are an expert at leveraging Chatham Financial tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Chatham Financial "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Chatham Financial MCP Server

Connect your Chatham Financial (ChathamDirect) account to any AI agent and take full control of your financial risk management and valuations through natural conversation. Streamline how you manage debt and derivatives.

When paired with CrewAI, Chatham Financial becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Chatham Financial tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Transaction Oversight — List and retrieve details for derivative and debt transactions natively
Valuation Intelligence — Access current and historical mark-to-market valuations flawlessly
Payment Tracking — Monitor payment schedules and history for all financial instruments securely
Market Data Access — Retrieve benchmark rates (SOFR, EURIBOR) and forward curves flawlessly
Hedge Accounting — Access hedge accounting details and effectiveness test results flawlessly
Entity Management — List all legal entities and portfolios configured in your account directly within your workspace

The Chatham Financial MCP Server exposes 8 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Chatham Financial to CrewAI via MCP

Follow these steps to integrate the Chatham Financial MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from Chatham Financial

Why Use CrewAI with the Chatham Financial MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Chatham Financial through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Chatham Financial + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Chatham Financial MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Chatham Financial for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Chatham Financial, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Chatham Financial tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Chatham Financial against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Chatham Financial MCP Tools for CrewAI (8)

These 8 tools become available when you connect Chatham Financial to CrewAI via MCP:

get_chatham_market_data

Retrieve benchmark rates and forward curves

get_hedge_effectiveness

Retrieve hedge effectiveness test results

get_trade_accounting

Get hedge accounting details for a transaction

get_trade_valuations

Get current and historical valuations for a trade

list_chatham_entities

List legal entities configured in the account

list_chatham_portfolios

List all managed portfolios

list_chatham_transactions

List financial transactions and trades

list_trade_payments

List payment schedules and history for a transaction

Example Prompts for Chatham Financial in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Chatham Financial immediately.

"Show me all active trades in my Chatham account."

"What is the latest valuation for trade ID 'T-98765'?"

"Show me the forward curve for 3-month SOFR."

Troubleshooting Chatham Financial MCP Server with CrewAI

Common issues when connecting Chatham Financial to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Chatham Financial + CrewAI FAQ

Common questions about integrating Chatham Financial MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.