How to Use the U.S. Treasury Budget — Federal Revenue, Spending & Deficit MCP in LlamaIndex

Q: Can LlamaIndex help me understand U.S. Treasury Budget — Federal Revenue, Spending & Deficit trends?

Yes. By indexing results from both getfederalspending and getfederalrevenue, you can run semantic searches across time periods to identify historical spending patterns or revenue dips.

Q: How do I use LlamaIndex with U.S. Treasury Budget — Federal Revenue, Spending & Deficit for daily operations?

Run getdailycashbalance and then index that output. Later, you can query the index to retrieve the exact cash balance from a specific date in the past, linking it directly to your knowledge base.

Q: Does LlamaIndex support U.S. Treasury Budget — Federal Revenue, Spending & Deficit multi-year comparison?

It does. You can pull prior year totals using getfederalspending and index the comparison data side-by-side with current results for comprehensive semantic search.

Build RAG applications with LlamaIndex for U.S. Treasury Budget — Federal Revenue, Spending & Deficit data.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect U.S. Treasury Budget — Federal Revenue, Spending & Deficit MCP to LlamaIndex

Create your Vinkius account to connect U.S. Treasury Budget — Federal Revenue, Spending & Deficit to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup U.S. Treasury Budget — Federal Revenue, Spending & Deficit with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index Daily Cash Balances

When you run `get_daily_cash_balance`, the resulting cash figure gets indexed into your vector store. This means you can query past operational balances against specific dates, even if they aren't in a document. Instead of just getting a number, LlamaIndex grounds that data point—the daily operating cash balance—in a searchable knowledge base for future reference.

Query Deficit and Surplus Trends

Use `get_deficit_surplus` to pull the fiscal year-to-date status. LlamaIndex makes this data part of your index, letting you ask complex questions like: 'What was the deficit trend in Q3?' The system doesn't just output a number; it provides context and source grounding based on past API calls.

Combine Spending and Revenue Data

You can combine results from `get_federal_revenue` (tax receipts) and `get_federal_spending` (outlays). LlamaIndex treats these separate data points as one unified knowledge resource. The resulting index allows you to ask highly specific questions, like 'How did Department X's spending compare to revenue in the last quarter?'

Setup guide

Set up U.S. Treasury Budget — Federal Revenue, Spending & Deficit MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all U.S. Treasury Budget — Federal Revenue, Spending & Deficit MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to U.S. Treasury Budget — Federal Revenue, Spending & Deficit tools.",
)
response = await agent.run("List recent U.S. Treasury Budget — Federal Revenue, Spending & Deficit data")

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 U.S. Department of the Treasury. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect U.S. Treasury Budget — Federal Revenue, Spending & Deficit now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about U.S. Treasury Budget — Federal Revenue, Spending & Deficit MCP in LlamaIndex

LlamaIndex ingests API tool outputs and turns them into a searchable index. You can query past results from `get_federal_revenue` or `get_deficit_surplus` as if they were written in a document.

Yes. By indexing results from both `get_federal_spending` and `get_federal_revenue`, you can run semantic searches across time periods to identify historical spending patterns or revenue dips.

Run `get_daily_cash_balance` and then index that output. Later, you can query the index to retrieve the exact cash balance from a specific date in the past, linking it directly to your knowledge base.

It does. You can pull prior year totals using `get_federal_spending` and index the comparison data side-by-side with current results for comprehensive semantic search.

The server touches transactional and aggregate financial records, including daily debt issuance/redemption amounts from `get_daily_debt_transactions`, cash balances, and spending by department.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript