How to Use the Wiagro MCP in LlamaIndex

Q: What kind of alerts can I search with Wiagro and LlamaIndex?

You can index rupture alerts from getrupturealerts. Instead of just seeing a list, you query the knowledge base to find every instance where structural damage was detected over time for specific silobags.

Q: Can LlamaIndex track facility-wide data using Wiagro?

Yes. After calling getfacilityoverview, that summary becomes a searchable document in your index. You can query the system about overall grain quality status across all units, long after the initial report was generated.

Q: If I need to know about historical humidity using Wiagro and LlamaIndex?

You use gethumidityhistory, and that time-series data gets indexed. This lets you query, for example, 'Show me all instances where condensation was detected in silobag 2 last month,' providing deep contextual answers.

Build knowledge bases with LlamaIndex: Search Wiagro's full history using LlamaIndex.

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Connect Wiagro MCP to LlamaIndex

Create your Vinkius account to connect Wiagro 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.

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Setup Wiagro with LlamaIndex

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Search historical spoilage trends with LlamaIndex

LlamaIndex takes the raw data from `get_co2_history` and indexes it, so you can search through months of readings instantly. You don't just get a graph; you query past sessions about whether CO2 was rising in silobag 5 last spring. This makes historical spoilage trend analysis searchable knowledge.

Assess quality status with LlamaIndex MCP Server

You can combine `get_quality_assessment` results with other metadata, like the details from `get_silobag_details`. By indexing this output into your vector store, you build an answer to 'what should I do about silobag 3' that combines current risk levels and container specifics.

Monitor sensor health using LlamaIndex

When you run `get_sensor_health`, the output isn't just a list; it becomes part of your indexed knowledge base. You can query past weeks to see when specific sensors were offline or if battery levels dropped below warning thresholds, making system maintenance easier.

Setup guide

Set up Wiagro 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 Wiagro 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 Wiagro tools.",
)
response = await agent.run("List recent Wiagro data")

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Common questions about Wiagro MCP in LlamaIndex

LlamaIndex indexes the results of every MCP tool call. This means when you query for data using Wiagro, the answers are grounded in actual API outputs—like current temperature or humidity readings.

You can index rupture alerts from `get_rupture_alerts`. Instead of just seeing a list, you query the knowledge base to find every instance where structural damage was detected over time for specific silobags.

Yes. After calling `get_facility_overview`, that summary becomes a searchable document in your index. You can query the system about overall grain quality status across all units, long after the initial report was generated.

You use `get_humidity_history`, and that time-series data gets indexed. This lets you query, for example, 'Show me all instances where condensation was detected in silobag 2 last month,' providing deep contextual answers.

This includes time-series sensor readings (temperature, humidity, CO2), quality scores, operational alerts, and detailed silobag metadata. Everything is indexed for semantic search.

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