Wiagro MCP Server for Claude Code 12 tools — connect in under 2 minutes
Claude Code is Anthropic's agentic CLI for terminal-first development. Add Wiagro as an MCP server in one command and Claude Code will discover every tool at runtime — ideal for automation pipelines, CI/CD integration, and headless workflows via the Vinkius.
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Vinkius supports streamable HTTP and SSE.
Vinkius Desktop App
The modern way to manage MCP Servers — no config files, no terminal commands. Install Wiagro and 2,500+ MCP Servers from a single visual interface.
# Your Vinkius token — get it at cloud.vinkius.com
claude mcp add wiagro --transport http "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
* 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 Wiagro MCP Server
Connect your Wiagro Smart Silobag API to any AI agent and take full control of IoT-based grain condition monitoring, rupture detection, satellite environmental monitoring, and silobag quality management through natural conversation.
Claude Code registers Wiagro as an MCP server in a single terminal command. Once connected, Claude Code discovers all 12 tools at runtime and can call them headlessly — ideal for CI/CD pipelines, cron jobs, and automated workflows where Wiagro data drives decisions without human intervention.
What you can do
- Silobag Management — List and manage all silobags and conventional silos with grain types, fill levels, and monitoring status
- Real-Time Readings — Get current temperature, intergranular humidity, and CO2 readings from IoT sensors throughout the grain mass
- Temperature History — Track historical temperature trends to detect hot spots and spoilage heating
- Humidity History — Monitor intergranular humidity patterns for moisture migration and condensation detection
- CO2 Tracking — Follow CO2 trends as the earliest indicator of biological activity and grain spoilage
- Rupture Detection — Receive satellite-based alerts for silobag tears, holes, and structural damage
- Alert Management — Monitor active alerts for high temperature, humidity, and CO2 threshold breaches
- Sensor Health — Track IoT sensor battery levels, signal strength, and operational status
- Satellite Monitoring — Access satellite-based environmental data affecting silobag conditions
- Quality Assessment — Get AI-powered grain quality scores with storage life predictions
- Facility Overview — Get comprehensive facility-wide summaries for executive reporting
The Wiagro MCP Server exposes 12 tools through the Vinkius. Connect it to Claude Code 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 Wiagro to Claude Code via MCP
Follow these steps to integrate the Wiagro MCP Server with Claude Code.
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
Add the MCP Server
Run the command above in your terminal
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
Start using Wiagro
Ask Claude: "Using Wiagro, show me..." — 12 tools are ready
Why Use Claude Code with the Wiagro MCP Server
Claude Code provides unique advantages when paired with Wiagro through the Model Context Protocol.
Single-command setup: `claude mcp add` registers the server instantly — no config files to edit or applications to restart
Terminal-native workflow means MCP tools integrate seamlessly into shell scripts, CI/CD pipelines, and automated DevOps tasks
Claude Code runs headlessly, enabling unattended batch processing using Wiagro tools in cron jobs or deployment scripts
Built by the same team that created the MCP protocol, ensuring first-class compatibility and the fastest adoption of new protocol features
Wiagro + Claude Code Use Cases
Practical scenarios where Claude Code combined with the Wiagro MCP Server delivers measurable value.
CI/CD integration: embed Wiagro tool calls in your deployment pipeline to validate configurations or fetch secrets before shipping
Headless batch processing: schedule Claude Code to query Wiagro nightly and generate reports without human intervention
Shell scripting: pipe Wiagro outputs into other CLI tools for data transformation, filtering, and aggregation
Infrastructure monitoring: run Claude Code in a cron job to query Wiagro status endpoints and alert on anomalies
Wiagro MCP Tools for Claude Code (12)
These 12 tools become available when you connect Wiagro to Claude Code via MCP:
get_alerts
Returns alert severity (critical, warning, info), alert type, affected silobag, timestamp, and recommended actions. Essential for proactive grain management, quality issue detection, and operational response. AI agents should use this when users ask "show me all active alerts", "what warnings have been triggered for silobag 3", or need alert data for operational monitoring. Optional silobag_id filters alerts for a specific silobag. Get active temperature, humidity, and CO2 alerts for silobags
get_co2_history
CO2 is the earliest indicator of biological activity (mold, insects, grain respiration) that leads to spoilage. Returns time-series CO2 data in ppm with timestamps. Essential for spoilage trend analysis, early warning detection, and validating storage condition stability. AI agents should reference this when users ask "show me CO2 trends for silobag 3 over the past 30 days", "has CO2 been rising in silobag 5", or need historical CO2 data for grain quality assessment. Get historical CO2 readings to track biological activity and spoilage trends
get_current_readings
Returns temperature (Celsius), intergranular humidity (%), and CO2 levels (ppm) from multiple sensor positions throughout the grain mass. Essential for real-time grain quality monitoring, early spoilage detection, and storage condition assessment. AI agents should use this when users ask "what are the current conditions in silobag 2", "show me all sensor readings for silobag 4", or need immediate grain quality data for storage management decisions. Get current temperature, humidity, and CO2 readings from sensors in a silobag
get_facility_overview
Essential for executive reporting, facility-wide quality assessment, and strategic storage management. AI agents should use this when users ask "give me an overview of my entire facility", "what is the overall grain quality status", or need facility-level summaries for management reporting. Get comprehensive overview of all monitored silobags and storage units
get_humidity_history
Humidity migration and condensation are key drivers of spoilage and quality loss. Returns time-series humidity data (%) with timestamps from multiple sensor positions. Essential for moisture migration analysis, condensation detection, and storage safety monitoring. AI agents should use this when users ask "show me humidity trends for silobag 1", "has humidity been stable in silobag 2", or need historical humidity data for storage management. Get historical intergranular humidity readings for moisture migration analysis
get_quality_assessment
Returns quality score, risk level, estimated remaining storage life, and recommended actions. Essential for grain quality monitoring, marketing timing decisions, and storage duration optimization. AI agents should reference this when users ask "what is the grain quality in silobag 3", "assess storage conditions for silobag 5", or need quality assessment data for storage management and marketing decisions. Get AI-powered grain quality assessment for a specific silobag
get_rupture_alerts
Rupture alerts indicate tears, holes, or structural damage to silobags that could expose grain to weather, pests, and spoilage. Returns alert severity, location of rupture, detection timestamp, and recommended actions. Essential for silobag integrity monitoring, grain protection, and preventing quality loss. AI agents should use this when users ask "are there any silobag ruptures detected", "show rupture alerts for silobag 3", or need structural integrity alerts for silobag management. Optional silobag_id filters alerts for a specific silobag. Get silobag rupture detection alerts for all silobags or a specific one
get_satellite_data
Essential for understanding external risk factors, weather impact assessment, and proactive silobag protection. AI agents should use this when users ask "what is the satellite data for silobag 2", "show external conditions affecting silobag 4", or need environmental context for silobag management decisions. Get satellite-based monitoring data for external silobag conditions
get_sensor_health
Returns sensor IDs, positions (depth/location), battery levels, signal strength, last communication time, and operational status (active, low battery, offline). Essential for sensor network maintenance, data continuity assurance, and monitoring system reliability. AI agents should reference this when users ask "are all sensors working in silobag 5", "which sensors need battery replacement", or need sensor network health data for system administration. Get health status of IoT sensors deployed in a silobag
get_silobag_details
Essential for understanding silobag context before analyzing sensor data, planning aeration strategies, or generating quality reports. AI agents should reference this when users ask "tell me about silobag 3", "what grain is stored in silobag 5", or need detailed silobag metadata for informed analysis. Get detailed information about a specific silobag or conventional silo
get_silobags
Returns silobag IDs, names, locations, grain types, fill levels, and current monitoring status. Essential for facility overview, silobag inventory management, and selecting specific silobags for detailed analysis. AI agents should use this when users ask "show me all my silobags", "list monitored storage units", or need to identify available silobags before querying sensor readings or alerts. List all silobags and conventional silos monitored by Wiagro
get_temperature_history
Temperature increases often indicate active spoilage, insect activity, or mold growth. Returns time-series temperature data (Celsius) with timestamps from multiple sensor depths and positions. Essential for hot spot detection, spoilage heating identification, and grain quality preservation. AI agents should reference this when users ask "show me temperature trends for silobag 4", "are there any hot spots developing in silobag 6", or need historical temperature data for spoilage analysis. Optional days parameter controls lookback period. Get historical temperature readings to detect hot spots and spoilage heating in a silobag
Example Prompts for Wiagro in Claude Code
Ready-to-use prompts you can give your Claude Code agent to start working with Wiagro immediately.
"Show me the current temperature, humidity, and CO2 readings for silobag 3."
"Check for any silobag rupture alerts or active warnings across my facility."
"Give me a quality assessment for all my monitored silobags."
Troubleshooting Wiagro MCP Server with Claude Code
Common issues when connecting Wiagro to Claude Code through the Vinkius, and how to resolve them.
Command not found: claude
npm install -g @anthropic-ai/claude-codeConnection timeout
Wiagro + Claude Code FAQ
Common questions about integrating Wiagro MCP Server with Claude Code.
How do I add an MCP server to Claude Code?
claude mcp add --transport http "" in your terminal. Claude Code registers the server and discovers all tools immediately.Can Claude Code run MCP tools in headless mode?
How do I list all connected MCP servers?
claude mcp in your terminal to see all registered servers and their status, or type /mcp inside an active Claude Code session.Connect Wiagro with your favorite client
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Connect Wiagro to Claude Code
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.