Chatham Financial MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Chatham Financial as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Chatham Financial. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Chatham Financial?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
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.
LlamaIndex agents combine Chatham Financial tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Chatham Financial MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 8 tools from Chatham Financial
Why Use LlamaIndex with the Chatham Financial MCP Server
LlamaIndex provides unique advantages when paired with Chatham Financial through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Chatham Financial tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Chatham Financial tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Chatham Financial, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Chatham Financial tools were called, what data was returned, and how it influenced the final answer
Chatham Financial + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Chatham Financial MCP Server delivers measurable value.
Hybrid search: combine Chatham Financial real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Chatham Financial to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Chatham Financial for fresh data
Analytical workflows: chain Chatham Financial queries with LlamaIndex's data connectors to build multi-source analytical reports
Chatham Financial MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Chatham Financial to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Chatham Financial to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpChatham Financial + LlamaIndex FAQ
Common questions about integrating Chatham Financial MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Chatham Financial with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Python SDK for building production-grade OpenAI agent workflows.
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TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Chatham Financial to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.