LeafEngines Agricultural Intelligence for Openclaw

LeafEngines is a high-performance MCP server providing agricultural data and soil intelligence tools for AI coding agents.

qwarranto
v1.1.2
Apr 30, 2026
0
793
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install leafengines

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install leafengines using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is LeafEngines Agricultural Intelligence?

LeafEngines is a specialized Model Context Protocol (MCP) server that empowers developers to integrate deep agricultural intelligence into their workflows. By utilizing these Openclaw Skills, users gain access to a suite of tools focused on soil analysis, crop recommendation, and hardware optimization. The skill is built on robust infrastructure, having served over a thousand developers since its launch.

The core value of LeafEngines lies in its ability to translate complex environmental data into actionable insights for AI agents. Whether you are building an automated farming assistant or conducting environmental research, this skill provides the necessary data bridge to make AI models agriculturally aware. It leverages Google's TurboQuant research to ensure that even complex agricultural calculations remain fast and memory-efficient on various hardware configurations.

LeafEngines Agricultural Intelligence Use Cases

  • Precision crop planning by analyzing soil characteristics for specific US counties.
  • Academic research and environmental impact assessments using localized agricultural data.
  • Development of AI-driven farming applications that require real-time soil and suitability insights.
  • Optimization of LLMs like Gemma 7B on edge devices using the built-in TurboQuant capabilities.
  • Verification of hardware performance for agricultural analysis tasks in offline or resource-constrained environments.

How LeafEngines Agricultural Intelligence Works

  1. The user provides a 5-digit county FIPS code to the AI agent to specify the geographic area of interest.
  2. The Openclaw Skills environment sends a request to the LeafEngines MCP server hosted on Supabase.
  3. The server authenticates the request via the x-free-tier header or a dedicated API key.
  4. LeafEngines retrieves specific soil data and processes crop suitability algorithms tailored to that location.
  5. Structured agricultural intelligence is returned to the agent, enabling it to provide expert-level farming recommendations or data summaries.

LeafEngines Agricultural Intelligence Setup

To integrate LeafEngines with your Openclaw Skills configuration, add the following to your MCP server settings.

For the Free Tier (no API key required):

mcpServers:
  leafengines:
    url: https://wzgnxkoeqzvueypwzvyn.supabase.co/functions/v1/mcp-server
    headers:
      x-free-tier: true

For Paid Tiers with full tool access:

mcpServers:
  leafengines:
    url: https://wzgnxkoeqzvueypwzvyn.supabase.co/functions/v1/mcp-server
    headers:
      x-api-key: YOUR_PAID_API_KEY_HERE

LeafEngines Agricultural Intelligence Data Schema & Taxonomy

LeafEngines organizes its agricultural intelligence through specialized parameters and headers. Below is the metadata taxonomy used by the skill:

Parameter Requirement Description
county_fips Required 5-digit county FIPS code (e.g., '13067' for Fulton County, GA)
x-free-tier Optional Header set to 'true' to enable the free evaluation tier
x-api-key Optional Header containing your paid subscription key for full tool access
api_key Optional Inline parameter alternative for authentication in specific tools

LeafEngines Agricultural Intelligence Advanced Features

  • TurboQuant integration providing 6x memory compression for LLM agricultural tasks.
  • 8x faster inference speeds for soil analysis and crop prediction workflows.
  • Support for low-memory environments, allowing Gemma 7B to run on 4GB devices.
  • Emergency API fallback system to ensure high availability for critical agricultural operations.
  • Seamless multi-platform support across Openclaw Skills, Claude Desktop, and n8n nodes.

SKILL.md


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