Can my AI predict when my silo will run empty based on current usage?

Yes! Use the `get_days_to_empty` tool with your silo ID. GrainSure AI analyzes current fill levels and historical usage patterns to predict exactly how many days until the silo runs empty, with a confidence score. For deeper analysis, combine with `get_usage_history` to see the consumption trends that drive the prediction. This gives you proactive warning to schedule deliveries before running out.

How do I set up low stock alerts for my silos?

Use the `update_silo_settings` tool to configure your low stock threshold percentage (e.g., 20% means alert when silo drops below 20% full). Then use `get_low_stock_alerts` to check for any active alerts. GrainSure will automatically monitor fill levels and trigger alerts when thresholds are breached, giving you timely warning to plan deliveries.

Can I create a delivery order directly through the API?

Yes! Use the `create_delivery_order` tool with the silo ID, quantity in tonnes, and optionally a preferred delivery date and supplier. The API will confirm your order with an order ID and estimated delivery date. You can also use `get_days_to_empty` predictions to automatically trigger orders when silos reach critical levels.

GrainSure MCP Server for VS Code Copilot 12 tools — connect in under 2 minutes

Name: GrainSure
Availability: InStock
Author: Vinkius

code.visualstudio.com/docs/copilot/chat/mcp-servers

Built by Vinkius GDPR 12 Tools IDE

GitHub Copilot in VS Code is the most widely adopted AI coding assistant, embedded directly into the world's most popular code editor. With MCP support in Agent mode, Copilot can access external data and APIs to generate context-aware code grounded in real-time information.

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The modern way to manage MCP Servers — no config files, no terminal commands. Install GrainSure and 2,500+ MCP Servers from a single visual interface.

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Classic Setup·json

{
  "mcpServers": {
    "grainsure": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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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 GrainSure MCP Server

Connect your GrainSure Silo Monitoring API to any AI agent and take full control of real-time grain fill level tracking, usage rate analysis, predictive days-to-empty forecasting, and automated delivery management through natural conversation.

GitHub Copilot Agent mode brings GrainSure data directly into your VS Code workflow. With a project-scoped config, the entire team shares access to 12 tools. Copilot queries live data, generates typed code, and writes tests from actual API responses, all without leaving the editor.

What you can do

Silo Management — List and manage all grain silos with current fill levels, grain types, and monitoring status
Real-Time Fill Levels — Get current grain fill percentage and remaining tonnes for each silo
Usage Tracking — Monitor historical grain consumption rates and identify usage trends
Days to Empty — Get AI-predicted days until each silo runs empty based on current usage patterns
Fill Level History — Track how fill levels have changed over time for delivery effectiveness analysis
Low Stock Alerts — Receive automated alerts when silo levels drop below configured thresholds
Delivery Orders — Create and manage grain delivery orders for timely inventory replenishment
Order History — Track past deliveries, quantities, and supplier performance
Sensor Health — Monitor IoT sensor battery levels, signal strength, and calibration status
Farm Overview — Get comprehensive farm-wide inventory summaries for executive reporting
Silo Settings — Customize alert thresholds, grain types, and usage rate assumptions

The GrainSure MCP Server exposes 12 tools through the Vinkius. Connect it to VS Code Copilot 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 GrainSure to VS Code Copilot via MCP

Follow these steps to integrate the GrainSure MCP Server with VS Code Copilot.

Create MCP config

Create a .vscode/mcp.json file in your project root

Add the server config

Paste the JSON configuration above

Enable Agent mode

Open GitHub Copilot Chat and switch to Agent mode using the dropdown

Start using GrainSure

Ask Copilot: "Using GrainSure, help me...". 12 tools available

Why Use VS Code Copilot with the GrainSure MCP Server

GitHub Copilot for Visual Studio Code provides unique advantages when paired with GrainSure through the Model Context Protocol.

VS Code is used by over 70% of developers. adding MCP tools to Copilot means your team can leverage external data without leaving their primary editor

Project-scoped MCP configs (`.vscode/mcp.json`) let you commit server configurations to your repository, ensuring the entire team shares the same tool access

Copilot's Agent mode integrates MCP tools seamlessly with file editing, terminal commands, and workspace search in a single agentic loop

GitHub's enterprise compliance and audit features extend to MCP tool usage, providing visibility into how AI interacts with external services

GrainSure + VS Code Copilot Use Cases

Practical scenarios where VS Code Copilot combined with the GrainSure MCP Server delivers measurable value.

Live API integration: Copilot can query an MCP server, inspect the response schema, and generate typed API client code in the same step

DevSecOps workflows: security teams can give developers access to domain intelligence tools directly in their editor for real-time vulnerability assessment during code review

Data pipeline development: Copilot fetches sample data via MCP and generates transformation scripts, validators, and test fixtures from actual API responses

Documentation generation: Copilot queries available tools and auto-generates README sections, API reference docs, and usage examples

GrainSure MCP Tools for VS Code Copilot (12)

These 12 tools become available when you connect GrainSure to VS Code Copilot via MCP:

create_delivery_order

Accepts delivery quantity (tonnes), preferred delivery date, supplier information, and any special instructions. Returns order confirmation with order ID, estimated delivery date, and tracking information. Essential for proactive inventory replenishment, automated ordering based on predictions, and supply chain management. AI agents should use this when users ask "order 20 tonnes of wheat for silo 3", "schedule a delivery for silo 5 next week", or need to place delivery orders based on low stock predictions. Create a new grain delivery order for a specific silo

get_current_level

Returns fill percentage, remaining tonnes, current level height, and last update timestamp. Essential for real-time inventory tracking, delivery planning, and stock management. AI agents should use this when users ask "what is the current fill level in silo 2", "how much grain is left in silo 4", or need immediate stock level data for feed planning and delivery decisions. Get real-time grain fill level for a specific silo

get_days_to_empty

Returns estimated days to empty, predicted empty date, confidence score, and usage rate assumptions. Essential for proactive delivery planning, preventing stock-outs, and optimizing supply chain timing. AI agents should use this when users ask "when will silo 3 run empty", "how many days of feed are left in silo 5", or need predictive supply data for delivery scheduling. Get AI-predicted days until a silo runs empty based on current usage patterns

get_farm_overview

Essential for executive reporting, farm-wide inventory assessment, and strategic supply planning. AI agents should use this when users ask "give me an overview of all my silos", "what is the total grain inventory across the farm", or need farm-level summaries for management reporting. Get comprehensive overview of all monitored silos on the farm

get_fill_level_history

Returns time-series fill percentage data with timestamps showing how stock levels have changed over time. Essential for fill trend analysis, delivery effectiveness assessment, and consumption pattern identification. AI agents should use this when users ask "show me fill level trends for silo 1 over the past 60 days", "has silo 2 been filling or depleting", or need historical fill data for inventory management. Optional days parameter controls lookback period. Get historical fill level readings for a specific silo

get_low_stock_alerts

Returns alert severity (critical, warning, info), affected silo, current fill percentage, threshold level, timestamp, and recommended actions. Essential for proactive inventory management, preventing stock-outs, and timely delivery ordering. AI agents should use this when users ask "show me all low stock alerts", "is silo 3 running low", or need alert data for inventory monitoring. Optional silo_id filters alerts for a specific silo. Get low stock alerts for silos or a specific silo

get_order_history

Essential for delivery tracking, supplier performance assessment, and inventory replenishment planning. AI agents should reference this when users ask "show me delivery history for silo 2", "when was the last delivery to silo 4", or need order data for supply chain analysis. Get delivery order history for a specific silo

get_sensor_health

Returns sensor battery level, signal strength, last communication time, calibration status, and operational status (active, low battery, offline, needs calibration). Essential for sensor maintenance, data continuity assurance, and monitoring system reliability. AI agents should reference this when users ask "is the sensor working in silo 5", "does silo 3 need sensor calibration", or need sensor health data for system administration. Get health status of the level monitoring sensor for a specific silo

get_silo_details

Essential for understanding silo context before analyzing usage data, planning deliveries, or generating inventory reports. AI agents should reference this when users ask "tell me about silo 3", "what grain is stored in silo 5", or need detailed silo metadata for informed decisions. Get detailed information about a specific grain silo

get_silos

Returns silo IDs, names, locations, grain types, current fill levels, and monitoring status. Essential for farm overview, silo inventory management, and selecting specific silos for detailed analysis. AI agents should use this when users ask "show me all my silos", "list monitored storage units", or need to identify available silos before querying fill levels or usage data. List all grain silos monitored by GrainSure

get_usage_history

Returns time-series usage data (tonnes per day/week) with timestamps. Essential for consumption trend analysis, feed rate calculation, and delivery timing optimization. AI agents should reference this when users ask "show me grain usage trends for silo 3", "what is the daily consumption rate for silo 5", or need historical usage data for feed planning and inventory forecasting. Optional days parameter controls lookback period. Get historical grain usage data for a specific silo

update_silo_settings

Essential for customizing monitoring behavior, adjusting alert sensitivity, and maintaining accurate silo profiles. AI agents should use this when users ask "change the low stock threshold for silo 3 to 20 percent", "update silo 5 grain type to barley", or need to modify silo monitoring configuration. Update silo monitoring settings including alert thresholds and grain type

Example Prompts for GrainSure in VS Code Copilot

Ready-to-use prompts you can give your VS Code Copilot agent to start working with GrainSure immediately.

"Show me the current fill levels for all my silos."

"How many days until my wheat silo runs empty?"

"Order 30 tonnes of barley for silo 2 with delivery next week."

Troubleshooting GrainSure MCP Server with VS Code Copilot

Common issues when connecting GrainSure to VS Code Copilot through the Vinkius, and how to resolve them.

MCP tools not available

Ensure you are in Agent mode in Copilot Chat. MCP tools only appear in Agent mode.

GrainSure + VS Code Copilot FAQ

Common questions about integrating GrainSure MCP Server with VS Code Copilot.

Which VS Code version supports MCP?

MCP support requires VS Code 1.99 or later with the GitHub Copilot extension. Ensure both are updated to the latest version. Older versions of Copilot may not expose the Agent mode toggle.

How do I switch to Agent mode?

Open the Copilot Chat panel and look for two mode options: "Ask" and "Agent". Click "Agent" to enable autonomous tool calling. In Ask mode, Copilot provides conversational answers but cannot invoke MCP tools.

Can I restrict which MCP tools Copilot can access?

Yes. VS Code shows a tool consent dialog before any MCP tool is invoked for the first time. You can also configure tool access policies at the organization level through GitHub Copilot settings.

Does MCP work in VS Code Remote or Codespaces?

Yes. MCP servers configured via .vscode/mcp.json work in Remote SSH, WSL, and GitHub Codespaces environments. The MCP connection is established from the remote host, so ensure the server URL is accessible from that environment.