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AgroLog MCP Server for Cline 11 tools — connect in under 2 minutes

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Cline is an autonomous AI coding agent inside VS Code that plans, executes, and iterates on tasks. Wire AgroLog through Vinkius and Cline gains direct access to every tool. from data retrieval to workflow automation. without leaving the terminal.

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Classic Setup·json
{
  "mcpServers": {
    "agrolog": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
AgroLog
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* 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 AgroLog MCP Server

Connect your AgroLog Grain Monitoring API to any AI agent and take full control of real-time temperature monitoring, moisture tracking, CO2 spoilage detection, crop level inventory, and automated aeration control through natural conversation.

Cline operates autonomously inside VS Code. it reads your codebase, plans a strategy, and executes multi-step tasks including AgroLog tool calls without waiting for prompts between steps. Connect 11 tools through Vinkius and Cline can fetch data, generate code, and commit changes in a single autonomous run.

What you can do

  • Temperature Monitoring — Get real-time grain temperature readings from sensors in silos and bins
  • Moisture Tracking — Monitor grain moisture content for safe storage and drying decisions
  • CO2 Detection — Detect elevated CO2 levels as early warning signs of spoilage and mold growth
  • Crop Level Inventory — Track grain volume and silo fill levels for inventory management
  • Weather Station Data — Access outdoor temperature, humidity, wind speed, and rainfall data
  • Device Management — List all monitoring devices and view their configuration attributes
  • Relay Control — Remotely control fans, aeration systems, and dryers connected to AgroLog devices
  • Alarm Monitoring — Track active alarms and alerts for proactive grain management
  • Historical Telemetry — Retrieve time-series sensor data for trend analysis and reporting
  • Multi-Customer Management — Manage devices across multiple farms or customer organizations

The AgroLog MCP Server exposes 11 tools through the Vinkius. Connect it to Cline 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 AgroLog to Cline via MCP

Follow these steps to integrate the AgroLog MCP Server with Cline.

01

Open Cline MCP Settings

Click the MCP Servers icon in the Cline sidebar panel

02

Add remote server

Click "Add MCP Server" and paste the configuration above

03

Enable the server

Toggle the server switch to ON

04

Start using AgroLog

Ask Cline: "Using AgroLog, help me...". 11 tools available

Why Use Cline with the AgroLog MCP Server

Cline provides unique advantages when paired with AgroLog through the Model Context Protocol.

01

Cline operates autonomously. it reads your codebase, plans a strategy, and executes multi-step tasks including MCP tool calls without step-by-step prompts

02

Runs inside VS Code, so you get MCP tool access alongside your existing extensions, terminal, and version control in a single window

03

Cline can create, edit, and delete files based on MCP tool responses, enabling end-to-end automation from data retrieval to code generation

04

Transparent execution: every tool call and file change is shown in Cline's activity log for full visibility and approval before committing

AgroLog + Cline Use Cases

Practical scenarios where Cline combined with the AgroLog MCP Server delivers measurable value.

01

Autonomous feature building: tell Cline to fetch data from AgroLog and scaffold a complete module with types, handlers, and tests

02

Codebase refactoring: use AgroLog tools to validate live data while Cline restructures your code to match updated schemas

03

Automated testing: Cline fetches real responses from AgroLog and generates snapshot tests or mocks based on actual payloads

04

Incident response: query AgroLog for real-time status and let Cline generate hotfix patches based on the findings

AgroLog MCP Tools for Cline (11)

These 11 tools become available when you connect AgroLog to Cline via MCP:

01

get_alarms

Alarms are triggered by threshold breaches (high temperature, high moisture, elevated CO2, equipment failure) and indicate conditions requiring immediate attention. Returns alarm severity (critical, warning, info), alarm type, affected device, timestamp, and acknowledgment status. Essential for proactive grain management, quality issue detection, and operational response. AI agents should use this when users ask "show me all active alarms", "what alerts have been triggered", or need alarm data for operational monitoring. Optional device_id filters alarms for a specific device. Get active and historical alarms/alerts from the AgroLog monitoring system

02

get_co2

Elevated CO2 levels indicate biological activity (mold growth, insect respiration, or grain respiration) and are early warning signs of spoilage before temperature changes become apparent. Returns timestamped CO2 value in ppm. Essential for early spoilage detection, grain quality monitoring, and proactive storage management. AI agents should use this when users ask "what is the CO2 level in silo 2", "check headspace gas readings for device X", or need early warning indicators of grain spoilage. Get CO2/headspace gas readings from a specific monitoring device

03

get_crop_level

Crop level sensors measure the grain volume or height in silos and bins, enabling inventory management and capacity planning. Returns timestamped crop level value (percentage or distance). Essential for grain inventory tracking, bin capacity management, and logistics planning. AI agents should reference this when users ask "how full is silo 4", "check crop level for device X", or need inventory data for storage management and logistics planning. Get grain crop level (volume/quantity) readings from a specific monitoring device

04

get_customer_devices

Returns device IDs, names, types, and status for the specified customer. Essential for multi-farm management, service provider operations, and organizational device administration. AI agents should use this when users ask "show me all devices for customer X", "list sensors for this farm organization", or need customer-scoped device inventory in multi-tenant deployments. List all monitoring devices for a specific customer/organization in multi-tenant setups

05

get_device_attributes

Essential for understanding device setup, sensor positioning within silos, and device management. AI agents should reference this when users ask "show me the configuration for this sensor", "what is the calibration data for device X", or need device metadata for system administration. Get configuration attributes and metadata for a specific monitoring device

06

get_device_telemetry

Supports custom key selection (temperature, moisture, co2, humidity, etc.) and configurable data point limits for historical analysis. Essential for trend analysis, condition monitoring over time, and creating data visualizations. AI agents should reference this when users ask "show me temperature history for device X over the last 48 hours", "get moisture trend for this sensor", or need historical telemetry data for grain management analysis. Get time-series telemetry data from a specific monitoring device with customizable keys and limits

07

get_devices

Returns device IDs, names, types (temperature sensor, moisture sensor, weather station, crop level monitor, headspace/CO2 sensor), labels, and current status. Essential for device inventory, system overview, and selecting specific sensors for telemetry queries. AI agents should use this when users ask "show me all sensors in my grain silo", "list monitoring devices", or need to identify available devices before querying temperature, moisture, or other telemetry data. List all AgroLog monitoring devices (temperature, moisture, weather sensors) in your system

08

get_moisture

Moisture content is the most critical factor for safe grain storage — high moisture leads to mold, spoilage, and heating. Returns timestamped moisture value as percentage. Essential for grain quality assessment, drying decisions, and storage safety monitoring. AI agents should reference this when users ask "what is the moisture level in bin 5", "check grain moisture for device X", or need moisture data for storage management and drying planning. Get current grain moisture readings from a specific monitoring device

09

get_temperature

Temperature is critical for detecting spoilage, mold growth, and insect activity in stored grain. Returns timestamped temperature value in Celsius. Essential for grain quality monitoring, spoilage prevention, and ventilation scheduling. AI agents should use this when users ask "what is the temperature in silo 3", "check grain temperature for device X", or need current temperature data for storage management decisions. Device IDs can be found using get_devices. Get current grain temperature readings from a specific monitoring device

10

get_weather

Essential for drying decisions (outdoor air conditions for natural air drying), harvest planning (rain forecasts, wind conditions), and understanding environmental impact on stored grain. Returns the latest 10 readings with timestamps. AI agents should use this when users ask "what are the current weather conditions at my facility", "show me wind speed and rainfall data", or need weather context for grain management decisions. Get weather station data (temperature, humidity, wind, rainfall) from a specific device

11

set_relay_state

Accepts device ID, relay name, and desired state (true=on, false=off). Essential for remote grain management, automated ventilation scheduling, and responding to temperature/moisture alerts. AI agents should use this when users ask "turn on the fan for silo 3", "activate aeration for bin 2", or need to remotely control ventilation equipment based on sensor readings. WARNING: Always verify current conditions before changing relay states. Control relay outputs (fans, aeration, dryers) connected to an AgroLog device

Example Prompts for AgroLog in Cline

Ready-to-use prompts you can give your Cline agent to start working with AgroLog immediately.

01

"Check the temperature and moisture in silo 3 and tell me if there is any spoilage risk."

02

"Show me all active alarms in my grain storage facility."

03

"What is the current crop level inventory across all my grain bins?"

Troubleshooting AgroLog MCP Server with Cline

Common issues when connecting AgroLog to Cline through the Vinkius, and how to resolve them.

01

Server shows error in sidebar

Click the server name to see logs. Verify the URL and token are correct.

AgroLog + Cline FAQ

Common questions about integrating AgroLog MCP Server with Cline.

01

How does Cline connect to MCP servers?

Cline reads MCP server configurations from its settings panel in VS Code. Add the server URL and Cline discovers all available tools on initialization.
02

Can Cline run MCP tools without approval?

By default, Cline asks for confirmation before executing tool calls. You can configure auto-approval rules for trusted servers in the settings.
03

Does Cline support multiple MCP servers at once?

Yes. Configure as many servers as needed. Cline can use tools from different servers within the same autonomous task execution.

Connect AgroLog to Cline

Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.