How do I get a USDA NASS API key?

Visit [**nass.usda.gov/developer**](https://www.nass.usda.gov/developer/index.php) and register for a free API key. The key is delivered instantly via the web form. It's completely free with no usage cost.

What crops and commodities are available?

The NASS Quick Stats database covers all major US agricultural commodities: CORN, SOYBEANS, WHEAT, COTTON, RICE, SORGHUM, OATS, BARLEY, HAY, PEANUTS, POTATOES for crops; CATTLE, HOGS, CHICKENS, TURKEYS, MILK, EGGS, HONEY for livestock; plus fruit, vegetables, nursery products and many more. Use `get_param_values` with param 'commodity' to see the complete list.

Can I filter data by state and year?

Yes! All query tools support optional state and year parameters. State can be the full name (e.g. 'IOWA') or abbreviation (e.g. 'IA'). Year accepts specific years (e.g. '2024') or ranges. The data returned includes the state, year, commodity, value and unit for each record.

What kind of economic data is available?

The ECONOMICS sector includes: prices received by farmers for crops and livestock, prices paid by farmers (inputs, feed, fuel), farm production expenses, farm real estate values, cash rent for cropland and pasture, and agricultural income data. Use `get_economics_data` to query by commodity, state and year.

USDA NASS MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: USDA NASS
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="USDA NASS Specialist",
    goal="Help users interact with USDA NASS effectively",
    backstory=(
        "You are an expert at leveraging USDA NASS 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 USDA NASS "
        "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)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 USDA NASS MCP Server

Connect to USDA NASS (National Agricultural Statistics Service) APIs through any AI agent and explore American agriculture data through natural conversation.

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

What you can do

Crop Production — Query yield, production, harvested acres and price data for all major crops (corn, soybeans, wheat, cotton, rice)
Livestock Data — Retrieve cattle inventory, hog production, poultry statistics, milk and egg production data
Agricultural Economics — Access prices received/paid by farmers, farm income, production expenses and land values
Farm Demographics — Explore Census of Agriculture data including operator age, experience, occupation and veteran status
Parameter Discovery — Discover valid values for any filter parameter (commodities, states, years, units)
Survey Metadata — Review information about all NASS surveys including frequencies and methodologies

The USDA NASS 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 USDA NASS to CrewAI via MCP

Follow these steps to integrate the USDA NASS 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 USDA NASS

Why Use CrewAI with the USDA NASS MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with USDA NASS 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 the 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

USDA NASS + CrewAI Use Cases

Practical scenarios where CrewAI combined with the USDA NASS MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries USDA NASS 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 USDA NASS, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain USDA NASS 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 USDA NASS against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

USDA NASS MCP Tools for CrewAI (8)

These 8 tools become available when you connect USDA NASS to CrewAI via MCP:

get_crop_summary

Requires a commodity name (e.g. CORN, SOYBEANS, WHEAT, COTTON). Optionally filter by state and year. Returns detailed statistics with units, geographic scope and time period. Get crop production summary from USDA NASS

get_demographics_data

Optionally filter by state and year. Sector is automatically set to DEMOGRAPHICS. Get farm demographics data from USDA NASS

get_economics_data

Optionally filter by commodity, state and year. Sector is automatically set to ECONOMICS. Get agricultural economics data from USDA NASS

get_livestock_summary

Requires a commodity name (e.g. CATTLE, HOGS, CHICKENS, MILK, EGGS). Optionally filter by state and year. Get livestock production summary from USDA NASS

get_param_values

Parameters include: sector, group, commodity, commodity_desc, short_desc, source_desc, util_desc, unit_desc, freq_desc, domain_desc, state, county. Use this to discover what values you can filter by before making queries. Get valid values for a Quick Stats parameter

get_quick_stats

Accepts parameters: sector (CROPS, ANIMALS & PRODUCTS, ECONOMICS, DEMOGRAPHICS), commodity, group, commodity_desc, state, year, freq (ANNUAL, MONTHLY), unit_desc, source_desc. Returns statistical data with value, unit, state, year and commodity information. Use get_param_values to discover valid parameter values before querying. Query USDA NASS Quick Stats database

get_survey_info

This is useful for understanding what data is available and how frequently it is collected. Get information about USDA NASS surveys

search_by_commodity

Optionally filter by state, year and sector. This is a broad search that returns all available data for the commodity, including production, price, inventory and acreage statistics. Search Quick Stats by commodity name

Example Prompts for USDA NASS in CrewAI

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

"Show me the corn production summary for Iowa in 2024."

"What are the current cattle inventory numbers for Texas?"

"Show me what commodity values are available for filtering."

Troubleshooting USDA NASS MCP Server with CrewAI

Common issues when connecting USDA NASS 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

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

USDA NASS + CrewAI FAQ

Common questions about integrating USDA NASS 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.