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Centaur Analytics MCP Server for Claude Code 12 tools — connect in under 2 minutes

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Claude Code is Anthropic's agentic CLI for terminal-first development. Add Centaur Analytics 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 Vinkius.

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# Your Vinkius token. get it at cloud.vinkius.com
claude mcp add centaur-analytics --transport http "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
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About Centaur Analytics MCP Server

Connect your Centaur Analytics Internet-of-Crops API to any AI agent and take full control of AI-powered grain quality monitoring, predictive spoilage detection, wireless sensor management, and enterprise grain storage intelligence through natural conversation.

Claude Code registers Centaur Analytics 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 Centaur Analytics data drives decisions without human intervention.

What you can do

  • Bin Management — List and manage all grain storage bins with fill levels, grain types, and monitoring status
  • Real-Time Readings — Get current CO2, moisture, and temperature readings from wireless sensors throughout the grain mass
  • CO2 Tracking — Monitor historical CO2 trends as the earliest indicator of biological activity and spoilage
  • Moisture Analysis — Track moisture content and migration patterns to detect condensation and quality risks
  • Temperature Monitoring — Detect hot spots and spoilage heating with distributed temperature sensor data
  • AI Spoilage Predictions — Receive machine learning-powered spoilage risk assessments with days-to-spoilage estimates
  • Quality Forecasting — Predict future grain quality metrics using computer simulation models
  • Alert Management — Monitor active alerts for high CO2, rising temperature, moisture issues, and sensor failures
  • Sensor Health — Track wireless sensor battery levels, signal strength, and operational status
  • Facility Overview — Get comprehensive facility-wide summaries for executive reporting and strategic management
  • Quality Reports — Generate AI-powered comprehensive quality reports with actionable recommendations

The Centaur Analytics 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 Centaur Analytics to Claude Code via MCP

Follow these steps to integrate the Centaur Analytics MCP Server with Claude Code.

01

Install Claude Code

Run npm install -g @anthropic-ai/claude-code if not already installed

02

Add the MCP Server

Run the command above in your terminal

03

Verify the connection

Run claude mcp to list connected servers, or type /mcp inside a session

04

Start using Centaur Analytics

Ask Claude: "Using Centaur Analytics, show me...". 12 tools are ready

Why Use Claude Code with the Centaur Analytics MCP Server

Claude Code provides unique advantages when paired with Centaur Analytics through the Model Context Protocol.

01

Single-command setup: `claude mcp add` registers the server instantly. no config files to edit or applications to restart

02

Terminal-native workflow means MCP tools integrate seamlessly into shell scripts, CI/CD pipelines, and automated DevOps tasks

03

Claude Code runs headlessly, enabling unattended batch processing using Centaur Analytics tools in cron jobs or deployment scripts

04

Built by the same team that created the MCP protocol, ensuring first-class compatibility and the fastest adoption of new protocol features

Centaur Analytics + Claude Code Use Cases

Practical scenarios where Claude Code combined with the Centaur Analytics MCP Server delivers measurable value.

01

CI/CD integration: embed Centaur Analytics tool calls in your deployment pipeline to validate configurations or fetch secrets before shipping

02

Headless batch processing: schedule Claude Code to query Centaur Analytics nightly and generate reports without human intervention

03

Shell scripting: pipe Centaur Analytics outputs into other CLI tools for data transformation, filtering, and aggregation

04

Infrastructure monitoring: run Claude Code in a cron job to query Centaur Analytics status endpoints and alert on anomalies

Centaur Analytics MCP Tools for Claude Code (12)

These 12 tools become available when you connect Centaur Analytics to Claude Code via MCP:

01

get_alerts

Alerts are triggered by threshold breaches (high CO2, rising temperature, moisture migration, sensor failures) and indicate conditions requiring immediate attention. Returns alert severity (critical, warning, info), alert type, affected bin, 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 bin 3", or need alert data for operational monitoring. Optional bin_id filters alerts for a specific bin. Get active alerts and warnings for grain bins or a specific bin

02

get_bin_details

Essential for understanding bin context before analyzing sensor data, planning aeration strategies, or generating quality reports. AI agents should reference this when users ask "tell me about bin 5", "what grain is stored in silo 3", or need detailed bin metadata for informed analysis. Get detailed information about a specific grain storage bin

03

get_bins

Returns bin IDs, names, locations, grain types, fill levels, and current monitoring status. Essential for facility overview, bin inventory management, and selecting specific bins for detailed analysis. AI agents should use this when users ask "show me all my grain bins", "list monitored storage units", or need to identify available bins before querying sensor readings or AI predictions. List all grain storage bins monitored by Centaur Analytics

04

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 bin 3 over the past 30 days", "has CO2 been rising in silo 5", or need historical CO2 data for grain quality assessment. Optional days parameter controls lookback period. Get historical CO2 readings to track spoilage trends over time

05

get_current_readings

Returns CO2 levels (ppm), moisture content (%), and temperature (C) 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 bin 2", "show me all sensor readings for silo 4", or need immediate grain quality data for storage management decisions. Get current CO2, moisture, and temperature readings from all sensors in a bin

06

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 the entire grain storage facility

07

get_moisture_history

Moisture migration and condensation are key drivers of spoilage and quality loss. Returns time-series moisture data (%) with timestamps from multiple sensor positions. Essential for moisture migration analysis, condensation detection, drying effectiveness assessment, and storage safety monitoring. AI agents should use this when users ask "show me moisture trends for bin 1", "has moisture been stable in silo 2", or need historical moisture data for storage management. Get historical moisture content readings for grain storage analysis

08

get_quality_forecast

Uses computer simulation models combining current sensor data, weather forecasts, and grain characteristics. Essential for marketing timing, quality preservation planning, and storage duration optimization. AI agents should reference this when users ask "what will the grain quality be in bin 2 next month", "forecast quality changes for silo 4", or need predictive quality data for marketing and storage decisions. Get AI-powered grain quality forecast for upcoming weeks

09

get_quality_report

Combines current sensor readings, historical trends, spoilage predictions, quality forecasts, and actionable recommendations into a single report. Includes test weight estimates, moisture stability analysis, temperature uniformity assessment, and mycotoxin risk evaluation. Essential for quality documentation, marketing decisions, insurance claims, and comprehensive grain condition assessment. AI agents should reference this when users ask "generate a quality report for bin 2", "give me the complete grain condition assessment for silo 4", or need comprehensive quality documentation for a specific bin. Get a comprehensive AI-generated quality report for a specific grain bin

10

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 bin 5", "which sensors need battery replacement", or need sensor network health data for system administration. Get health status and battery levels of wireless sensors in a grain bin

11

get_spoilage_predictions

Returns spoilage risk level (low, moderate, high, critical), predicted days until spoilage onset, confidence scores, and recommended preventive actions. Essential for proactive grain management, early intervention planning, and quality preservation. AI agents should use this when users ask "what is the spoilage risk for bin 3", "when will grain quality degrade in silo 5", or need AI-driven risk assessments for storage management decisions. Get AI-powered spoilage risk predictions for a specific grain bin

12

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, aeration effectiveness evaluation, and grain quality preservation. AI agents should reference this when users ask "show me temperature trends for bin 4", "are there any hot spots developing in silo 6", or need historical temperature data for spoilage analysis. Get historical temperature readings to detect hot spots and spoilage heating

Example Prompts for Centaur Analytics in Claude Code

Ready-to-use prompts you can give your Claude Code agent to start working with Centaur Analytics immediately.

01

"Show me the current CO2, moisture, and temperature readings for bin 5."

02

"What is the AI spoilage prediction for my soybean bin?"

03

"Give me a facility-wide overview of all grain bins and any active alerts."

Troubleshooting Centaur Analytics MCP Server with Claude Code

Common issues when connecting Centaur Analytics to Claude Code through the Vinkius, and how to resolve them.

01

Command not found: claude

Ensure Claude Code is installed globally: npm install -g @anthropic-ai/claude-code
02

Connection timeout

Check your internet connection and verify the Edge URL is reachable

Centaur Analytics + Claude Code FAQ

Common questions about integrating Centaur Analytics MCP Server with Claude Code.

01

How do I add an MCP server to Claude Code?

Run claude mcp add --transport http "" in your terminal. Claude Code registers the server and discovers all tools immediately.
02

Can Claude Code run MCP tools in headless mode?

Yes. Claude Code supports non-interactive execution, making it ideal for scripts, cron jobs, and CI/CD pipelines that need MCP tool access.
03

How do I list all connected MCP servers?

Run claude mcp in your terminal to see all registered servers and their status, or type /mcp inside an active Claude Code session.

Connect Centaur Analytics to Claude Code

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.