How to Use the USAspending (Federal Spending) MCP in CrewAI

Q: Can I get comprehensive reports on USAspending (Federal Spending) with CrewAI?

Yes. You set up a 'Reporting Agent' to execute downloadsearch and then have a 'Validation Agent' check the status using getdownloadstatus. This creates an autonomous reporting pipeline.

Q: How does USAspending (Federal Spending) use recipient identifiers with CrewAI?

Agents use tools like getrecipient based on an identifier. The specialized nature of CrewAI ensures that the agent knows exactly which data fields to pull and how to structure them for analysis.

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Connect USAspending (Federal Spending) MCP to CrewAI

Create your Vinkius account to connect USAspending (Federal Spending) to CrewAI 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 USAspending (Federal Spending) with CrewAI

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Perplexity

Run specialized research on award recipients.

Set up a 'Research Agent' that uses `list_recipients` and `get_recipient` to build an exhaustive list of grant recipients. A second 'Analysis Agent' can then use `search_spending_by_category` to filter those results. The CrewAI framework lets these agents collaborate, sharing memory until the final report is built.

Model complex spending comparisons.

You can assign an 'Orchestration Agent' to run `get_agency_awards` for multiple agencies and then have a 'Comparison Agent' use that data set. This allows you to compare obligations across different federal bodies. The hierarchical execution means the agents work in sequence, passing structured JSON results from one tool to the next.

Track spending by time or location.

A dedicated 'Data Agent' can run `search_spending_by_geography` for a specific state, while another agent runs `search_spending_over_time` to provide historical context. These two streams of data are then combined. The crew structure ensures that the outputs from these distinct geographic and temporal queries are presented together in one final output.

Setup guide

Set up USAspending (Federal Spending) MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke USAspending (Federal Spending) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="USAspending (Federal Spending) Analyst",
    goal="Access and analyze USAspending (Federal Spending) data via MCP.",
    backstory="Expert analyst with direct USAspending (Federal Spending) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent USAspending (Federal Spending) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="USAspending (Federal Spending) Analyst",
        goal="Access and analyze USAspending (Federal Spending) data via MCP.",
        backstory="Expert analyst with direct USAspending (Federal Spending) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent USAspending (Federal Spending) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

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 USAspending. 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 USAspending (Federal Spending) MCP in CrewAI

CrewAI runs multiple specialized agents. You can deploy a 'Discovery Agent' that uses `get_agency_overview` while another agent monitors the results, letting you analyze agency details without manual intervention.

Yes. You set up a 'Reporting Agent' to execute `download_search` and then have a 'Validation Agent' check the status using `get_download_status`. This creates an autonomous reporting pipeline.

Absolutely. You can create a workflow where one agent queries `get_disaster_overview` and another summarizes the findings, providing immediate insights into emergency funds.

Agents use tools like `get_recipient` based on an identifier. The specialized nature of CrewAI ensures that the agent knows exactly which data fields to pull and how to structure them for analysis.

This server touches structured federal award and transaction data, including agency budgetary resources, recipient names, and geographic spending metrics.

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