# dssat-mcp

> Use this tool when you need to interact with the DSSAT crop model using natural language, enabling simulation, calibration, and sensitivity analysis. It solves problems related to complex crop modeling by providing an intuitive interface for users to input parameters and receive outputs. The tool accepts natural language inputs and produces simulation results as outputs, ideal for use cases where ease of use and accessibility are crucial for crop modeling tasks.

Canonical page: https://skillsregistry.net/skills/beomseokforwork-dssat-mcp  
JSON: https://api.skillsregistry.net/v1/skills/beomseokforwork-dssat-mcp

## Description

Enables natural language interaction with the DSSAT crop model for simulation, calibration, and sensitivity analysis through LLM agents.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/o2n7fyxx8a)
- **Repository:** <https://github.com/BeomseokForWork/dssat-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "beomseokforwork-dssat-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/beomseokforwork-dssat-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/beomseokforwork-dssat-mcp/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt