How to Use the Wiagro MCP in CrewAI

Q: How does Wiagro integrate with CrewAI for complex tasks?

You define roles: one agent gathers data (e.g., calling getalerts), and a second, specialized agent acts on that information. The whole process runs autonomously as a collaborative team.

Q: Can CrewAI monitor both internal and external risks?

Yes. One agent can query the facility status using getfacilityoverview, while another simultaneously calls getsatellitedata to check for environmental impacts, giving a holistic view.

Q: Does Wiagro support tracking sensor network health with CrewAI?

Absolutely. An agent can run getsensorhealth and then automatically flag any sensors that report low battery or offline status, initiating a maintenance task without human oversight.

Run autonomous operations on Wiagro data using CrewAI multi-agent teams.

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Connect Wiagro MCP to CrewAI

Create your Vinkius account to connect Wiagro 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 Wiagro with CrewAI

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Autonomous Alert and Status Monitoring

You don't just run a single query. You build a team. The 'Monitor Agent' can use `get_alerts` to check for issues, while the 'Action Agent' uses that data to decide on next steps—like recommending aeration or reporting necessary maintenance. CrewAI’s shared memory means all agents work off the same source of truth, keeping operations seamless and highly accurate.

Deep Grain Quality Analysis with MCP Server

Set up a team where one agent runs `get_co2_history` for trend analysis. A second agent takes that data, cross-references it with the current readings from `get_current_readings`, and generates a final assessment score. The role-based specialization allows you to assign specific tools—like `get_quality_assessment` or `get_temperature_history`—to agents best equipped to handle them.

Facility Assessment Pipeline

The 'Coordinator Agent' runs first, calling `get_silobags` for a list. Then, the 'Reporting Agent' cycles through that list, calling `get_silobag_details` and gathering all necessary metadata in one autonomous run. This pipeline handles large-scale inventory checks or comprehensive assessments without manual iteration.

Setup guide

Set up Wiagro 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 Wiagro tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Wiagro 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="Wiagro Analyst",
        goal="Access and analyze Wiagro data via MCP.",
        backstory="Expert analyst with direct Wiagro access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Wiagro 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 Wiagro. 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 Wiagro MCP in CrewAI

You define roles: one agent gathers data (e.g., calling `get_alerts`), and a second, specialized agent acts on that information. The whole process runs autonomously as a collaborative team.

Yes. One agent can query the facility status using `get_facility_overview`, while another simultaneously calls `get_satellite_data` to check for environmental impacts, giving a holistic view.

Absolutely. An agent can run `get_sensor_health` and then automatically flag any sensors that report low battery or offline status, initiating a maintenance task without human oversight.

The team approach is ideal. You can assign one agent the task of listing all silos via `get_silobags`, and then sequentially run checks on each unit using other tools.

This server touches sensor readings (temperature, CO2, humidity), quality scores, and silobag metadata. All operational monitoring is managed through a single endpoint token for secure access.

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