How to Use the MAPA (Agricultura) MCP in CrewAI

Q: How do I set up a research agent for MAPA (Agricultura) in CrewAI?

You pass the MCP URL into the agent's mcps parameter. You then assign tools like searchpackages to the agent's tool list.

Deploy autonomous agent crews to research Brazilian agriculture with MAPA (Agricultura) and CrewAI.

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Connect MAPA (Agricultura) MCP to CrewAI

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Setup MAPA (Agricultura) with CrewAI

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Perplexity

Autonomous research crews with CrewAI

Assign one agent to `search_packages` and another to `get_resource` for deep dives into agricultural reports. They share memory to build a complete picture without your input. This approach lets your crew handle complex queries. One agent finds the package, the other extracts the resource link, and a third summarizes the findings.

Role-based data access

Give your Analyst agent access to `get_package` while keeping `list_organizations` restricted to the Monitor agent. You control the scope of each crew member. This is how you enforce discipline in your agents. You delegate specific tools to specific roles, ensuring your agents only do what they are designed for.

Hierarchical execution

Structure your agents so that a Manager agent reviews the results from `list_packages` before instructing the Researcher agent to fetch details. It keeps the crew focused. You define the hierarchy in your CrewAI configuration. The MCP Server acts as the data provider for every member of your team.

Setup guide

Set up MAPA (Agricultura) 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 MAPA (Agricultura) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent MAPA (Agricultura) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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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="MAPA (Agricultura) Analyst",
        goal="Access and analyze MAPA (Agricultura) data via MCP.",
        backstory="Expert analyst with direct MAPA (Agricultura) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent MAPA (Agricultura) 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 MAPA (Agricultura). 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 MAPA (Agricultura) MCP in CrewAI

You pass the MCP URL into the agent's `mcps` parameter. You then assign tools like `search_packages` to the agent's tool list.

Yes. They use shared memory to pass dataset IDs retrieved by one agent to another agent that needs to inspect the resource metadata.

It is efficient for querying government records. You can run multiple agents concurrently to parse different categories of agricultural data.

CrewAI handles the error and lets you define a fallback task for the agent. You can specify a retry or a different tool execution.

The server only interacts with public Brazilian government APIs. No sensitive or private data is ever involved in these tool calls.

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